From b87e72df7d104dbc10ccbaa15e50197e2387c60b Mon Sep 17 00:00:00 2001 From: zenalapp Date: Mon, 2 Oct 2023 17:05:24 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20duke-mal?= =?UTF-8?q?aria-collaboratory/bistro@821d4efb75e47def04b280c42e96f6ca04754?= =?UTF-8?q?3e6=20=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- apple-touch-icon-120x120.png | Bin 11456 -> 11456 bytes apple-touch-icon-152x152.png | Bin 15451 -> 15451 bytes apple-touch-icon-180x180.png | Bin 19005 -> 19005 bytes apple-touch-icon-60x60.png | Bin 5009 -> 5009 bytes apple-touch-icon-76x76.png | Bin 6380 -> 6380 bytes apple-touch-icon.png | Bin 19005 -> 19005 bytes articles/bistro.html | 9 +++++---- favicon-16x16.png | Bin 1227 -> 1227 bytes favicon-32x32.png | Bin 2470 -> 2470 bytes pkgdown.yml | 2 +- search.json | 2 +- 11 files changed, 7 insertions(+), 6 deletions(-) diff --git a/apple-touch-icon-120x120.png b/apple-touch-icon-120x120.png index 0604e05e211ef6e86801ef70c5a963d8fb2210af..847e59197418b5ce38128c14984b9e95fc2a5ce3 100644 GIT binary patch delta 78 zcmX>Qc_4B^B_|h?AdA?lf)|T6HnnL>7#ipr7=;*`TN#*G85wCC7+4t?yyk0}K3PFW P6078_U>ohpfjapBu74IS delta 78 zcmX>Qc_4B^B_}6`7^|w{OOqoTo7%J`3@mjGEJBQotPD)8jLo$T46F;kHzf>2X diff --git a/apple-touch-icon-180x180.png b/apple-touch-icon-180x180.png index 4097862a4f150c83786efaf33489cbfbc0e1efb2..99e3ebb80c3696a9365d54c098a071396b0f8c83 100644 GIT binary patch delta 80 zcmdlxg>ml`#tD_2Tug#2622#nF5TF~>?vVrple_hVrXt8Z{ym@ Sb3G-oO8#u-6r6m{GamrsKo~&) delta 80 zcmdlxg>ml`#tD_2oE&1T8u1Yxl^dIwJtYh*bqy>+jEt-dOsz}|v<(cb3=FED)>cfO S>nVv225hCVv!? P#40IvJKt!sl5jo%Dl-(Y delta 78 zcmbQJK2d!_B_}6`7_0J$u8AKvHiZjG7+C5WScDiESs9pG8JlVw7+4t?C`&{ioBUBo P602m8>*K1)O2YX7c+?f( diff --git a/apple-touch-icon-76x76.png b/apple-touch-icon-76x76.png index 22b7b8bb52a3e3f4906d710be4df59e1568772b7..deb1ff4d25a6ac9fa84d26c99803817436b2c5b9 100644 GIT binary patch delta 78 zcmaE3_{MNTB_|h?Ad9GRO`F6e3=MP*j6w{}tqe@8j109646Fh($ delta 78 zcmaE3_{MNTB_}6`7^_OyJC>l0O`F6e3@mjGEJBQotPD)8jLozS46Fml`#tD_2Tug#2Qj3o*>D<`F>?vVrple_hVrXtml`#tD_2oE&1Tni}yH?>9CvdrBBs>Ka&t7#Ud^m|B?_Y8x0>85rE1RCZ?a STu(`?l55VNE0}!FGamrVj~MU( diff --git a/articles/bistro.html b/articles/bistro.html index 5c2cec3..a2c41f2 100644 --- a/articles/bistro.html +++ b/articles/bistro.html @@ -162,8 +162,9 @@

Bloodmeal STR profiles (The bloodmeal STR profiles dataset should have one row per allele for each bloodmeal and marker, and include the allele peak height. Homozygous markers should only be included once (i.e. as one row). It -must have four columns named SampleName, Marker, Allele, and Height. -Here is an example included with bistro:

+must have four columns named SampleName, Marker, Allele, and Height. The +SampleName column should hold character values. Here is an example +included with bistro:

 head(bloodmeal_profiles)
 #>   SampleName   Marker Allele Height
@@ -185,8 +186,8 @@ 
Human STR profiles (human_profi
 bloodmeal STR profiles dataset - it should have one row per allele for
 each human and marker, but does not require peak heights. Again,
 homozygous markers should only be included once. The dataset must have
-three columns named SampleName, Marker, and Allele. Here is an
-example:

+three columns named SampleName, Marker, and Allele. The SampleName
+column should hold character values. Here is an example:

 
 head(human_profiles)
 #>                         SampleName   Marker Allele
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delta 80
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delta 98
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kTH+c}l9E`GYL%Oxl9^V?U}Ruqtcy* Loading required package: euroformix"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"required-inputs","dir":"Articles","previous_headings":"","what":"Required inputs","title":"Introduction to using bistro","text":"run bistro() using example data, let’s learn required inputs. Two required, one optional often recommended, datasets required run bistro(): bloodmeal human STR profiles required, human population allele frequencies optional. two required inputs STR genotyping kit name bloodmeal STR allele peak height threshold.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"bloodmeal-str-profiles-bloodmeal_profiles","dir":"Articles","previous_headings":"Required inputs","what":"Bloodmeal STR profiles (bloodmeal_profiles)","title":"Introduction to using bistro","text":"bloodmeal STR profiles dataset one row per allele bloodmeal marker, include allele peak height. Homozygous markers included (.e. one row). must four columns named SampleName, Marker, Allele, Height. example included bistro: example dataset, 4 different bloodmeals:","code":"head(bloodmeal_profiles) #>   SampleName   Marker Allele Height #> 1      evid1     AMEL      X   2136 #> 2      evid1     AMEL      Y   1015 #> 3      evid1 D10S1248     13   1856 #> 4      evid1 D10S1248     14    155 #> 5      evid1 D10S1248     15   1045 #> 6      evid1  D12S391     18    297 unique(bloodmeal_profiles$SampleName) #> [1] \"evid1\" \"evid2\" \"evid3\" \"evid4\""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"human-str-profiles-human_profiles","dir":"Articles","previous_headings":"Required inputs","what":"Human STR profiles (human_profiles)","title":"Introduction to using bistro","text":"human STR profiles dataset takes similar format bloodmeal STR profiles dataset - one row per allele human marker, require peak heights. , homozygous markers included . dataset must three columns named SampleName, Marker, Allele. example: example dataset, 3 different human profiles:","code":"head(human_profiles) #>                         SampleName   Marker Allele #> 1 00-JP0001-14_20142342311_NO-3241     AMEL      X #> 2 00-JP0001-14_20142342311_NO-3241     AMEL      Y #> 3 00-JP0001-14_20142342311_NO-3241 D10S1248     12 #> 4 00-JP0001-14_20142342311_NO-3241 D10S1248     13 #> 5 00-JP0001-14_20142342311_NO-3241  D12S391     17 #> 6 00-JP0001-14_20142342311_NO-3241  D12S391     18 unique(human_profiles$SampleName) #> [1] \"00-JP0001-14_20142342311_NO-3241\" \"P1\"                               #> [3] \"P2\""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"str-genotyping-kit-kit","dir":"Articles","previous_headings":"Required inputs","what":"STR genotyping kit (kit)","title":"Introduction to using bistro","text":"bistro requires input STR genotyping kit name. euroformix package includes kit parameters 23 common STR genotyping kits. also includes handy function list available kits: kit used genotype samples available defaults, modify kit.txt within euroformix package appropriate kit parameters. required parameters can usually found kit manufacturer’s documentation website.","code":"getKit() #>  [1] \"testkit\"       \"ESX16\"         \"ESX17\"         \"ESX17Fast\"     #>  [5] \"ESI17Fast\"     \"Fusion\"        \"Fusion 6C\"     \"SGMPlus\"       #>  [9] \"Identifiler\"   \"NGM\"           \"NGMSElect\"     \"NGMDetect\"     #> [13] \"GlobalFiler\"   \"PowerPlex16\"   \"PowerPlex21\"   \"24plex\"        #> [17] \"ESSPlex\"       \"ESSplexPlus\"   \"ESSplexSEPlus\" \"ESSplexSEQS\"   #> [21] \"ForenSeq\"      \"VFP\"           \"MiniFiler\""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"bloodmeal-allele-peak-threshold-peak_thresh","dir":"Articles","previous_headings":"Required inputs","what":"Bloodmeal allele peak threshold (peak_thresh)","title":"Introduction to using bistro","text":"bistro() also requires bloodmeal allele peak threshold (RFUs) provided. peaks heights threshold removed matching. prior filtering performed bloodmeal profiles based peak height, number equal greater threshold.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"human-population-allele-frequencies-pop_allele_freqs","dir":"Articles","previous_headings":"Required inputs","what":"Human population allele frequencies (pop_allele_freqs)","title":"Introduction to using bistro","text":"Human population frequencies allele locus may supplied. prefer, population allele frequencies can computed human STR profiles (see details). Note latter option suggested small set human reference profiles used. euroformix website provides publicly available population frequency datasets. Additionally, can get United States population allele frequencies many alleles NIST. like input population allele frequencies, dataset contain one column STR marker one row allele. alleles listed first column dataset column named “Allele”. entries marker-allele combination population allele frequency NA allele exist marker. example loci PowerPlex ESX 17 System (ESX17) kit.","code":"head(pop_allele_freqs) #>   Allele D3S1358        TH01 D21S11       D18S51 D10S1248 D1S1656 D2S1338 #> 1    5.0      NA 0.002598441     NA           NA       NA      NA      NA #> 2    6.0      NA 0.209274435     NA           NA       NA      NA      NA #> 3    6.3      NA          NA     NA           NA       NA      NA      NA #> 4    7.0      NA 0.212472516     NA 0.0008984726       NA      NA      NA #> 5    8.0      NA 0.083649810     NA           NA       NA      NA      NA #> 6    8.2      NA          NA     NA           NA       NA      NA      NA #>        D16S539 D22S1045 VWA    D8S1179 FGA D2S441 D12S391 D19S433        SE33 #> 1           NA       NA  NA         NA  NA     NA      NA      NA          NA #> 2 0.0008992806       NA  NA         NA  NA     NA      NA      NA          NA #> 3           NA       NA  NA         NA  NA     NA      NA      NA          NA #> 4           NA       NA  NA         NA  NA     NA      NA      NA          NA #> 5 0.0086930456       NA  NA 0.01130226  NA     NA      NA      NA          NA #> 6           NA       NA  NA         NA  NA     NA      NA      NA 0.002506945"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"running-bistro","dir":"Articles","previous_headings":"","what":"Running bistro()","title":"Introduction to using bistro","text":"Now enough background run bistro(), let’s test using example data included package: ’ll notice bunch messages print screen: One markers (AMEL) kit pop_allele_freqs. 6 peaks 200 RFU threshold removed, filtering one bloodmeals peaks remaining threshold. Notification log10LRs (log10 likelihood ratios) calculated bloodmeal-human pair (4 bloodmeals 3 humans). can take , progress also printed . Notification matches identified. Let’s take look output: output contains 8 columns: bloodmeal_id: bloodmeal sample name. est_noc: estimated number contributors (NOCs) bloodmeal. equals one, ’s predicted single-source bloodmeal; greater one, ’s predicted multi-source bloodmeal. Note sources mean humans . locus_count: number loci STR-typed bloodmeal. match: whether bloodmeal STR profile matched human database (yes ). human_id: human match bloodmeal (NA match). log10_lr: log10 likelihood ratio bloodmeal-human match (NA match). numerator log10LR likelihood person bitten bloodmeal denominator likelihood someone else bitten bloodmeal. notes: bloodmeal doesn’t match (see details). thresh_low: log10LR threshold match made. important thing notice , even though 4 bloodmeals, 5 rows output dataset. , bloodmeal appear least dataset, multiple rows present bloodmeals match multiple people (one row per match). example, , evid1 matches 2 different people (P1 P2) Please keep mind performing data analysis. notes column provides information match: passed filters: match. > min NOC matches: matches expected resolved. can happen closely related people human reference dataset. shared alleles: people human reference dataset alleles overlapped alleles bloodmeal. log10LRs < 1.5: none log10LRs high enough considered match. euroformix error: euroformix::contLikSearch() function run successfully. often happens incomplete bloodmeal profiles (.e. markers succesfully STR-typed). peaks threshold: bloodmeal STR peaks peak height threshold. timed : log-likelihood took long calculate. want give time, can modify time_limit argument (see ).","code":"bistro_output <- bistro(   bloodmeal_profiles = bloodmeal_profiles,   human_profiles = human_profiles,   pop_allele_freqs = pop_allele_freqs,   kit = \"ESX17\",   peak_thresh = 200 ) #> 1/17 markers in kit but not in pop_allele_freqs: AMEL #> Formatting bloodmeal profiles #> Removing 6 peaks under the threshold of 200 RFU. #> For 1/4 bloodmeal ids, all peaks are below the threshold #> Formatting human profiles #> Markers being used: D10S1248, D12S391, D16S539, D18S51, D19S433, D1S1656, D21S11, D22S1045, D2S1338, D2S441, D3S1358, D8S1179, FGA, SE33, TH01, VWA #> Calculating log10LRs #> # bloodmeal ids: 3 #> # human ids: 3 #> Bloodmeal id 1/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Bloodmeal id 2/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Bloodmeal id 3/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Identifying matches bistro_output #> # A tibble: 4 × 8 #>   bloodmeal_id locus_count est_noc match human_id log10_lr notes      thresh_low #>                                          #> 1 evid1                 16       2 yes   P1           21.8 passed al…        9.5 #> 2 evid1                 16       2 yes   P2           10.3 passed al…        9.5 #> 3 evid2                  1       2 no    NA           NA   all log10…       NA   #> 4 evid3                  8       1 no    NA           NA   all log10…       NA"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"using-computed-population-allele-frequencies","dir":"Articles","previous_headings":"","what":"Using computed population allele frequencies","title":"Introduction to using bistro","text":"want population allele frequencies computed inputted human reference profiles, must set calc_allele_freqs = TRUE: Note , use builtin dataset example , recommend using method human dataset 3 people. example may make sense relatively comprehensive set human reference profiles study site.","code":"bistro(   bloodmeal_profiles = bloodmeal_profiles,   human_profiles = human_profiles,   calc_allele_freqs = TRUE,   kit = \"ESX17\",   peak_thresh = 200 )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"running-bistro-on-a-subset-of-samples","dir":"Articles","previous_headings":"","what":"Running bistro() on a subset of samples","title":"Introduction to using bistro","text":"bistro() can take long time run, especially many samples closely related reference population. Therefore, running samples, highly recommend testing small subset samples make sure everything working expect. , can use bloodmeal_ids human_ids arguments tell bistro() ids want compare: can also useful like parallelize bistro(), example using workflow manager Snakemake NextFlow. ’d like try , template Snakemake pipeline running bistro. highly recommend planning run many samples.","code":"bistro(   bloodmeal_profiles = bloodmeal_profiles,   human_profiles = human_profiles,   pop_allele_freqs = pop_allele_freqs,   kit = \"ESX17\",   peak_thresh = 200,   bloodmeal_ids = c(\"evid1\", \"evid2\"),   human_ids = \"P1\" )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"other-arguments","dir":"Articles","previous_headings":"","what":"Other arguments","title":"Introduction to using bistro","text":"arguments can modify running bistro() include: Used bistro: rm_twins: whether remove identical STR profiles likely twins prior identifying matches. Note matches people resolved (default: TRUE) time_limit: longest amount time allowed calculate log-likelihood one bloodmeal-human pair, minutes (default: 3) Used euroformix::contLikSearch() calculating log-likelihoods: rm_markers: markers use calculating LRs. default, AMEL removed standard use calculating LRs sex-specific marker model_degrad: whether model peak degradation (default: TRUE) model_bw_stutt model_fw_stutt: whether model peak backward forward stutter (default: FALSE) difftol: difference tolerance log-likelihood across 2 iterations (default: 1) threads: number threads use computing log-likelihoods (default: 4) seed: seed reproducible results (default: 1) return_lr: whether return bloodmeal-human log10LRs. useful want investigate matches perform static threshold matching (see ) (default: FALSE)","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"other-matching-algorithms","dir":"Articles","previous_headings":"","what":"Other matching algorithms","title":"Introduction to using bistro","text":"also implemented matching algorithms including: match_exact(): Exact matching markers alleles match_similarity(): Similarity matching based highest similarity value humans reference database match_static_threshold(): Matching based static log10LR threshold. algorithms take similar inputs bistro(), case match_static_threshold(), bistro() output. Look upcoming manuscript comparison methods.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Zena Lapp. Author, maintainer. Christine Markwalter. Author.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Lapp Z, Markwalter C (2023). bistro: Bloodmeal identification STR overlap. https://duke-malaria-collaboratory.github.io/bistro/, https://github.com/duke-malaria-collaboratory/bistro.","code":"@Manual{,   title = {bistro: Bloodmeal identification by STR overlap},   author = {Zena Lapp and Christine Markwalter},   year = {2023},   note = {https://duke-malaria-collaboratory.github.io/bistro/, https://github.com/duke-malaria-collaboratory/bistro}, }"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/index.html","id":"bistro-bloodmeal-identification-by-str-overlap-","dir":"","previous_headings":"","what":"Bloodmeal identification by STR overlap","title":"Bloodmeal identification by STR overlap","text":"Functions allow identification matches bloodmeals people bit using short tandem repeat (STR) profiles human blood freshly fed bloodmeals people.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Bloodmeal identification by STR overlap","text":"can install bistro like :","code":"# install.packages(\"remotes\") remotes::install_github(\"duke-malaria-collaboratory/bistro\")"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/index.html","id":"dependencies","dir":"","previous_headings":"","what":"Dependencies:","title":"Bloodmeal identification by STR overlap","text":"Depends: R (>= 4.0.0), euroformix (>= 4.0.7) Imports: codetools (>= 0.2.19), dplyr (>= 1.1.3), R.utils (>= 2.12.2), stringr (>= 1.5.0), tibble (>= 3.2.1), tidyr (>= 1.3.0) Suggests: knitr (>= 1.43), readr (>= 2.1.4), rmarkdown (>= 2.24), testthat (>= 3.0.0)","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Bloodmeal identification by STR overlap","text":"Check vignette information.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bistro.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify human contributors to a bloodmeal using STR profiles — bistro","title":"Identify human contributors to a bloodmeal using STR profiles — bistro","text":"Identifies matches bloodmeal STR profiles database human STR profiles. euroformix::contLikSearch() function used calculate log10 likelihood ratios (log10_lrs) used identify human contributors bloodmeal. details present , see vignette('bistro').","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bistro.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify human contributors to a bloodmeal using STR profiles — bistro","text":"","code":"bistro(   bloodmeal_profiles,   human_profiles,   kit,   peak_thresh,   pop_allele_freqs = NULL,   calc_allele_freqs = FALSE,   bloodmeal_ids = NULL,   human_ids = NULL,   rm_twins = TRUE,   rm_markers = c(\"AMEL\"),   model_degrad = TRUE,   model_bw_stutt = FALSE,   model_fw_stutt = FALSE,   difftol = 1,   threads = 4,   seed = 1,   time_limit = 3,   return_lrs = FALSE )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bistro.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify human contributors to a bloodmeal using STR profiles — bistro","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. kit STR kit name euroformix. see list kits embedded euroformix use euroformix::getKit(). kit included, see vignette(\"bistro\") details include kit. peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). pop_allele_freqs Data frame first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA. NULL calc_allele_freqs = TRUE, population allele frequencies calculated human_profiles. calc_allele_freqs boolean indicating whether calculate allele frequencies human_profiles. FALSE, pop_allele_freqs input required. Default: FALSE bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL human_ids Vector human ids SampleName column human_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL rm_twins boolean indicating whether remove likely twins (identical STR profiles) human database prior identifying matches. Default: TRUE rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations. model_degrad boolean indicating whether model peak degradation. Used modelDegrad argument euroformix::contLikSearch(). Default: TRUE model_bw_stutt boolean indicating whether model peak backward stutter. Used modelBWstutt argument euroformix::contLikSearch(). Default: FALSE model_fw_stutt boolean indicating whether model peak forward stutter. Used modelFWstutt argument euroformix::contLikSearch(). Default: FALSE difftol Tolerance difference log likelihoods across 2 iterations. euroformix::contLikSearch() argument. Default: 1 threads Number threads use calculating log10_lrs. euroformix::contLikSearch() argument. Default: 4 seed Seed calculating log10_lrs. euroformix::contLikSearch() argument. Default: 1 time_limit Time limit minutes run euroformix::contLikSearch() function 1 bloodmeal-human pair. Default: 3 return_lrs boolean indicating whether return log10LRs bloodmeal-human pairs. Default: FALSE","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bistro.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify human contributors to a bloodmeal using STR profiles — bistro","text":"Tibble matches bloodmeal-human pairs including columns listed . Note multiple matches found bloodmeal, included separate rows. bloodmeal_id: bloodmeal id locus_count: number loci successfully typed bloodmeal est_noc: estimated number contributors bloodmeal match: whether match identified given bloodmeal (yes ) human_id: match, human id (NA otherwise) log10_lr: match, log10 likelihood ratio (NA otherwise) notes: bloodmeal match return_lrs = TRUE, named list length 2 returned: matches - tibble described lrs - log10LRs bloodmeal-human pair including columns described additional column: efm_noc, number contributors used input euroformix, min(est_noc, 3).","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bistro.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Identify human contributors to a bloodmeal using STR profiles — bistro","text":"","code":"bistro(bloodmeal_profiles, human_profiles,   pop_allele_freqs = pop_allele_freqs,   kit = \"ESX17\", peak_thresh = 200 ) #> 1/17 markers in kit but not in pop_allele_freqs: AMEL #> Formatting bloodmeal profiles #> Removing 6 peaks under the threshold of 200 RFU. #> For 1/4 bloodmeal ids, all peaks are below the threshold #> Formatting human profiles #> Markers being used: D10S1248, D12S391, D16S539, D18S51, D19S433, D1S1656, D21S11, D22S1045, D2S1338, D2S441, D3S1358, D8S1179, FGA, SE33, TH01, VWA #> Calculating log10LRs #> # bloodmeal ids: 3 #> # human ids: 3 #> Bloodmeal id 1/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Bloodmeal id 2/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Bloodmeal id 3/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Identifying matches #> # A tibble: 4 × 8 #>   bloodmeal_id locus_count est_noc match human_id log10_lr notes      thresh_low #>                                          #> 1 evid1                 16       2 yes   P1           21.8 passed al…        9.5 #> 2 evid1                 16       2 yes   P2           10.3 passed al…        9.5 #> 3 evid2                  1       2 no    NA           NA   all log10…       NA   #> 4 evid3                  8       1 no    NA           NA   all log10…       NA"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bloodmeal_profiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Bloodmeal STR profiles — bloodmeal_profiles","title":"Bloodmeal STR profiles — bloodmeal_profiles","text":"Example \"bloodmeal\" STR profiles EuroForMix","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bloodmeal_profiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bloodmeal STR profiles — bloodmeal_profiles","text":"","code":"bloodmeal_profiles"},{"path":[]},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bloodmeal_profiles.html","id":"bloodmeal-profiles","dir":"Reference","previous_headings":"","what":"bloodmeal_profiles","title":"Bloodmeal STR profiles — bloodmeal_profiles","text":"data frame 69 rows 4 columns: SampleName Human sample identifier Marker STR marker Allele STR allele Height STR peak height","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bloodmeal_profiles.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Bloodmeal STR profiles — bloodmeal_profiles","text":"http://euroformix.com/","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_allele_freqs.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate allele frequencies — calc_allele_freqs","title":"Calculate allele frequencies — calc_allele_freqs","text":"Calculate allele frequencies (generally human) population.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_allele_freqs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate allele frequencies — calc_allele_freqs","text":"","code":"calc_allele_freqs(human_profiles, rm_markers = NULL)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_allele_freqs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate allele frequencies — calc_allele_freqs","text":"human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_allele_freqs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate allele frequencies — calc_allele_freqs","text":"tibble first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_log10_lrs.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate log10_lrs for multiple bloodmeal-human pairs — calc_log10_lrs","title":"Calculate log10_lrs for multiple bloodmeal-human pairs — calc_log10_lrs","text":"Note function preprocess bloodmeal human profile data. like preprocess way performed internally bistro() function, must run prep_bloodmeal_profiles() prep_human_profiles() first.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_log10_lrs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate log10_lrs for multiple bloodmeal-human pairs — calc_log10_lrs","text":"","code":"calc_log10_lrs(   bloodmeal_profiles,   human_profiles,   pop_allele_freqs,   kit,   peak_thresh,   bloodmeal_ids = NULL,   human_ids = NULL,   model_degrad = TRUE,   model_bw_stutt = FALSE,   model_fw_stutt = FALSE,   difftol = 1,   threads = 4,   seed = 1,   time_limit = 3 )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_log10_lrs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate log10_lrs for multiple bloodmeal-human pairs — calc_log10_lrs","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. pop_allele_freqs Data frame first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA. NULL calc_allele_freqs = TRUE, population allele frequencies calculated human_profiles. kit STR kit name euroformix. see list kits embedded euroformix use euroformix::getKit(). kit included, see vignette(\"bistro\") details include kit. peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL human_ids Vector human ids SampleName column human_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL model_degrad boolean indicating whether model peak degradation. Used modelDegrad argument euroformix::contLikSearch(). Default: TRUE model_bw_stutt boolean indicating whether model peak backward stutter. Used modelBWstutt argument euroformix::contLikSearch(). Default: FALSE model_fw_stutt boolean indicating whether model peak forward stutter. Used modelFWstutt argument euroformix::contLikSearch(). Default: FALSE difftol Tolerance difference log likelihoods across 2 iterations. euroformix::contLikSearch() argument. Default: 1 threads Number threads use calculating log10_lrs. euroformix::contLikSearch() argument. Default: 4 seed Seed calculating log10_lrs. euroformix::contLikSearch() argument. Default: 1 time_limit Time limit minutes run euroformix::contLikSearch() function 1 bloodmeal-human pair. Default: 3","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_log10_lrs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate log10_lrs for multiple bloodmeal-human pairs — calc_log10_lrs","text":"tibble output bistro(), except match column every bloodmeal-human pair calculated log10_lr included. additional column efm_noc number contributors used euroformix::contLikSearch(). maximum value 3.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_one_log10_lr.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate log10_lr for one bloodmeal-human pair — calc_one_log10_lr","title":"Calculate log10_lr for one bloodmeal-human pair — calc_one_log10_lr","text":"Calculate log10_lr one bloodmeal-human pair","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_one_log10_lr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate log10_lr for one bloodmeal-human pair — calc_one_log10_lr","text":"","code":"calc_one_log10_lr(   bloodmeal_profiles,   bloodmeal_id,   human_profiles,   human_id,   pop_allele_freqs,   kit,   peak_thresh,   model_degrad = TRUE,   model_bw_stutt = FALSE,   model_fw_stutt = FALSE,   difftol = 1,   threads = 4,   seed = 1,   time_limit = 3 )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_one_log10_lr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate log10_lr for one bloodmeal-human pair — calc_one_log10_lr","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. bloodmeal_id Bloodmeal id SampleName column bloodmeal_profiles compute log10_lr human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. human_id Human id SampleName column human_profiles compute log10_lr pop_allele_freqs Data frame first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA. NULL calc_allele_freqs = TRUE, population allele frequencies calculated human_profiles. kit STR kit name euroformix. see list kits embedded euroformix use euroformix::getKit(). kit included, see vignette(\"bistro\") details include kit. peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). model_degrad boolean indicating whether model peak degradation. Used modelDegrad argument euroformix::contLikSearch(). Default: TRUE model_bw_stutt boolean indicating whether model peak backward stutter. Used modelBWstutt argument euroformix::contLikSearch(). Default: FALSE model_fw_stutt boolean indicating whether model peak forward stutter. Used modelFWstutt argument euroformix::contLikSearch(). Default: FALSE difftol Tolerance difference log likelihoods across 2 iterations. euroformix::contLikSearch() argument. Default: 1 threads Number threads use calculating log10_lrs. euroformix::contLikSearch() argument. Default: 4 seed Seed calculating log10_lrs. euroformix::contLikSearch() argument. Default: 1 time_limit Time limit minutes run euroformix::contLikSearch() function 1 bloodmeal-human pair. Default: 3","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_one_log10_lr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate log10_lr for one bloodmeal-human pair — calc_one_log10_lr","text":"tibble log10_lr bloodmeal-human pair including bloodmeal_id, human_id, locus_count (number STR loci used matching), est_noc (estimated number contributors), efm_noc (number contributors used euroformix), log10_lr (log10 likelihood ratio), notes","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_bistro_inputs.html","id":null,"dir":"Reference","previous_headings":"","what":"Check bistro inputs — check_bistro_inputs","title":"Check bistro inputs — check_bistro_inputs","text":"Check bistro inputs","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_bistro_inputs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check bistro inputs — check_bistro_inputs","text":"","code":"check_bistro_inputs(   bloodmeal_profiles,   human_profiles,   kit,   peak_thresh,   pop_allele_freqs,   calc_allele_freqs,   bloodmeal_ids,   human_ids,   rm_twins,   rm_markers,   model_degrad,   model_bw_stutt,   model_fw_stutt,   difftol,   threads,   seed,   time_limit,   return_lrs )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_bistro_inputs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check bistro inputs — check_bistro_inputs","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. kit STR kit name euroformix. see list kits embedded euroformix use euroformix::getKit(). kit included, see vignette(\"bistro\") details include kit. peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). pop_allele_freqs Data frame first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA. NULL calc_allele_freqs = TRUE, population allele frequencies calculated human_profiles. calc_allele_freqs boolean indicating whether calculate allele frequencies human_profiles. FALSE, pop_allele_freqs input required. Default: FALSE bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL human_ids Vector human ids SampleName column human_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL rm_twins boolean indicating whether remove likely twins (identical STR profiles) human database prior identifying matches. Default: TRUE rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations. model_degrad boolean indicating whether model peak degradation. Used modelDegrad argument euroformix::contLikSearch(). Default: TRUE model_bw_stutt boolean indicating whether model peak backward stutter. Used modelBWstutt argument euroformix::contLikSearch(). Default: FALSE model_fw_stutt boolean indicating whether model peak forward stutter. Used modelFWstutt argument euroformix::contLikSearch(). Default: FALSE difftol Tolerance difference log likelihoods across 2 iterations. euroformix::contLikSearch() argument. Default: 1 threads Number threads use calculating log10_lrs. euroformix::contLikSearch() argument. Default: 4 seed Seed calculating log10_lrs. euroformix::contLikSearch() argument. Default: 1 time_limit Time limit minutes run euroformix::contLikSearch() function 1 bloodmeal-human pair. Default: 3 return_lrs boolean indicating whether return log10LRs bloodmeal-human pairs. Default: FALSE","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_bistro_inputs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check bistro inputs — check_bistro_inputs","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_calc_allele_freqs.html","id":null,"dir":"Reference","previous_headings":"","what":"Check calc_allele_freqs — check_calc_allele_freqs","title":"Check calc_allele_freqs — check_calc_allele_freqs","text":"Check calc_allele_freqs","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_calc_allele_freqs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check calc_allele_freqs — check_calc_allele_freqs","text":"","code":"check_calc_allele_freqs(calc_allele_freqs)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_calc_allele_freqs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check calc_allele_freqs — check_calc_allele_freqs","text":"calc_allele_freqs boolean indicating whether calculate allele frequencies human_profiles. FALSE, pop_allele_freqs input required. Default: FALSE","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_calc_allele_freqs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check calc_allele_freqs — check_calc_allele_freqs","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_colnames.html","id":null,"dir":"Reference","previous_headings":"","what":"Check column names — check_colnames","title":"Check column names — check_colnames","text":"Check column names","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_colnames.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check column names — check_colnames","text":"","code":"check_colnames(df, expected_colnames)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_colnames.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check column names — check_colnames","text":"df Dataframe check expected_colnames Column names required resent","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_colnames.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check column names — check_colnames","text":"Nothing error","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_heights.html","id":null,"dir":"Reference","previous_headings":"","what":"Check peak_thresh — check_heights","title":"Check peak_thresh — check_heights","text":"Check peak_thresh","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_heights.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check peak_thresh — check_heights","text":"","code":"check_heights(heights, peak_thresh)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_heights.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check peak_thresh — check_heights","text":"heights vector peak heights peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch().","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_heights.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check peak_thresh — check_heights","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_ids.html","id":null,"dir":"Reference","previous_headings":"","what":"Check input ids — check_ids","title":"Check input ids — check_ids","text":"Check input ids","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_ids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check input ids — check_ids","text":"","code":"check_ids(vec, vec_name)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_ids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check input ids — check_ids","text":"vec vector check vec_name vector name","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_ids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check input ids — check_ids","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_if_allele_freqs.html","id":null,"dir":"Reference","previous_headings":"","what":"Check calc_if_allele_freqs — check_if_allele_freqs","title":"Check calc_if_allele_freqs — check_if_allele_freqs","text":"Check calc_if_allele_freqs","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_if_allele_freqs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check calc_if_allele_freqs — check_if_allele_freqs","text":"","code":"check_if_allele_freqs(pop_allele_freqs, calc_allele_freqs, kit_df)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_if_allele_freqs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check calc_if_allele_freqs — check_if_allele_freqs","text":"pop_allele_freqs Data frame first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA. NULL calc_allele_freqs = TRUE, population allele frequencies calculated human_profiles. calc_allele_freqs boolean indicating whether calculate allele frequencies human_profiles. FALSE, pop_allele_freqs input required. Default: FALSE kit_df Kit dataframe euroformix::getKit()","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_if_allele_freqs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check calc_if_allele_freqs — check_if_allele_freqs","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_bool.html","id":null,"dir":"Reference","previous_headings":"","what":"Check is boolean — check_is_bool","title":"Check is boolean — check_is_bool","text":"Check boolean","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_bool.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check is boolean — check_is_bool","text":"","code":"check_is_bool(vec, vec_name)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_bool.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check is boolean — check_is_bool","text":"vec vector check vec_name vector name","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_bool.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check is boolean — check_is_bool","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_numeric.html","id":null,"dir":"Reference","previous_headings":"","what":"Check is numeric — check_is_numeric","title":"Check is numeric — check_is_numeric","text":"Check numeric","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_numeric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check is numeric — check_is_numeric","text":"","code":"check_is_numeric(vec, vec_name, pos = FALSE)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_numeric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check is numeric — check_is_numeric","text":"vec vector check vec_name vector name pos whether number must positive","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_numeric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check is numeric — check_is_numeric","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_kit.html","id":null,"dir":"Reference","previous_headings":"","what":"Check kit — check_kit","title":"Check kit — check_kit","text":"Check kit","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_kit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check kit — check_kit","text":"","code":"check_kit(kit)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_kit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check kit — check_kit","text":"kit STR kit name euroformix. see list kits embedded euroformix use euroformix::getKit(). kit included, see vignette(\"bistro\") details include kit.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_kit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check kit — check_kit","text":"Error kit exist, dataframe kit otherwise","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_peak_thresh.html","id":null,"dir":"Reference","previous_headings":"","what":"Check peak_thresh — check_peak_thresh","title":"Check peak_thresh — check_peak_thresh","text":"Check peak_thresh","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_peak_thresh.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check peak_thresh — check_peak_thresh","text":"","code":"check_peak_thresh(peak_thresh)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_peak_thresh.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check peak_thresh — check_peak_thresh","text":"peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch().","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_peak_thresh.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check peak_thresh — check_peak_thresh","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_setdiff_markers.html","id":null,"dir":"Reference","previous_headings":"","what":"Check what markers are present — check_setdiff_markers","title":"Check what markers are present — check_setdiff_markers","text":"Check markers present","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_setdiff_markers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check what markers are present — check_setdiff_markers","text":"","code":"check_setdiff_markers(markers1, markers2, markers1_name, markers2_name)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_setdiff_markers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check what markers are present — check_setdiff_markers","text":"markers1 first vector check markers2 second vector check markers1_name first vector name markers2_name second vector name","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_setdiff_markers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check what markers are present — check_setdiff_markers","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/filter_peaks.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter peak heights that are under threshold — filter_peaks","title":"Filter peak heights that are under threshold — filter_peaks","text":"Filter peak heights threshold","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/filter_peaks.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter peak heights that are under threshold — filter_peaks","text":"","code":"filter_peaks(bloodmeal_profiles, peak_thresh)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/filter_peaks.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter peak heights that are under threshold — filter_peaks","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch().","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/filter_peaks.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter peak heights that are under threshold — filter_peaks","text":"Filtered dataframe","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_allele_freqs.html","id":null,"dir":"Reference","previous_headings":"","what":"Format population allele frequencies — format_allele_freqs","title":"Format population allele frequencies — format_allele_freqs","text":"Format population allele frequencies input euroformix contLikSearch() function.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_allele_freqs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format population allele frequencies — format_allele_freqs","text":"","code":"format_allele_freqs(pop_allele_freqs)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_allele_freqs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format population allele frequencies — format_allele_freqs","text":"pop_allele_freqs Data frame first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA. NULL calc_allele_freqs = TRUE, population allele frequencies calculated human_profiles.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_allele_freqs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format population allele frequencies — format_allele_freqs","text":"list allele frequencies population format required input euroformix contLikSearch() function","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_bloodmeal_profiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Format bloodmeal STR profiles — format_bloodmeal_profiles","title":"Format bloodmeal STR profiles — format_bloodmeal_profiles","text":"Format bloodmeal STR profiles input euroformix contLikSearch() function.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_bloodmeal_profiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format bloodmeal STR profiles — format_bloodmeal_profiles","text":"","code":"format_bloodmeal_profiles(bloodmeal_profiles)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_bloodmeal_profiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format bloodmeal STR profiles — format_bloodmeal_profiles","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_bloodmeal_profiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format bloodmeal STR profiles — format_bloodmeal_profiles","text":"list lists including alleles sample format required input euroformix contLikSearch() function.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_human_profiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Format human STR profiles — format_human_profiles","title":"Format human STR profiles — format_human_profiles","text":"Format human STR profiles input euroformix contLikSearch() function.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_human_profiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format human STR profiles — format_human_profiles","text":"","code":"format_human_profiles(human_profiles)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_human_profiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format human STR profiles — format_human_profiles","text":"human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_human_profiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format human STR profiles — format_human_profiles","text":"list lists including alleles sample format required input euroformix contLikSearch() function","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_bloodmeal_human_similarity.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify matches between bloodmeal and human STR profiles\nbased on similarity values — get_bloodmeal_human_similarity","title":"Identify matches between bloodmeal and human STR profiles\nbased on similarity values — get_bloodmeal_human_similarity","text":"Identify matches bloodmeal human STR profiles based similarity values","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_bloodmeal_human_similarity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify matches between bloodmeal and human STR profiles\nbased on similarity values — get_bloodmeal_human_similarity","text":"","code":"get_bloodmeal_human_similarity(bloodmeal_profiles, human_profiles)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_bloodmeal_human_similarity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify matches between bloodmeal and human STR profiles\nbased on similarity values — get_bloodmeal_human_similarity","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_bloodmeal_human_similarity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify matches between bloodmeal and human STR profiles\nbased on similarity values — get_bloodmeal_human_similarity","text":"dataframe two columns: bloodmeal_id: bloodmeal ID human_id: human ID match, \"match\" match","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_human_similarity.html","id":null,"dir":"Reference","previous_headings":"","what":"Get pairwise human STR profile similarities — get_human_similarity","title":"Get pairwise human STR profile similarities — get_human_similarity","text":"Get pairwise human STR profile similarities","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_human_similarity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get pairwise human STR profile similarities — get_human_similarity","text":"","code":"get_human_similarity(human_profiles)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_human_similarity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get pairwise human STR profile similarities — get_human_similarity","text":"human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_human_similarity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get pairwise human STR profile similarities — get_human_similarity","text":"Dataframe three columns: hu1: human ID 1 hu2: human ID 2 similarity: similarity value (# exact locus matches / # loci)","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/human_profiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Human reference database — human_profiles","title":"Human reference database — human_profiles","text":"Example human STR profiles EuroForMix","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/human_profiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Human reference database — human_profiles","text":"","code":"human_profiles"},{"path":[]},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/human_profiles.html","id":"human-profiles","dir":"Reference","previous_headings":"","what":"human_profiles","title":"Human reference database — human_profiles","text":"data frame 96 rows 3 columns: SampleName Human sample identifier Marker STR marker Allele STR allele","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/human_profiles.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Human reference database — human_profiles","text":"http://euroformix.com/","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_matches.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify matches for multiple bloodmeal-human pairs — identify_matches","title":"Identify matches for multiple bloodmeal-human pairs — identify_matches","text":"Identify matches multiple bloodmeal-human pairs","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_matches.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify matches for multiple bloodmeal-human pairs — identify_matches","text":"","code":"identify_matches(log10_lrs, bloodmeal_ids = NULL)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_matches.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify matches for multiple bloodmeal-human pairs — identify_matches","text":"log10_lrs Output calc_log10_lrs() bistro return_lrs = TRUE (lrs: second element list) bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_matches.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify matches for multiple bloodmeal-human pairs — identify_matches","text":"tibble output bistro().","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_one_match_set.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify matches between a bloodmeal and human references — identify_one_match_set","title":"Identify matches between a bloodmeal and human references — identify_one_match_set","text":"Identify matches bloodmeal human references","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_one_match_set.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify matches between a bloodmeal and human references — identify_one_match_set","text":"","code":"identify_one_match_set(log10_lrs, bloodmeal_id)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_one_match_set.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify matches between a bloodmeal and human references — identify_one_match_set","text":"log10_lrs output calc_log10_lrs() bloodmeal_id Bloodmeal id SampleName column bloodmeal_profiles compute log10_lr","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_one_match_set.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify matches between a bloodmeal and human references — identify_one_match_set","text":"tibble matches bloodmeal-human pairs including bloodmeal_id, locus_count (number STR loci used matching), est_noc (estimated number contributors), match, human_id (match), log10_lr (log10 likelihood ratio), notes","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_exact.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify exact matches between bloodmeal and human STR profiles — match_exact","title":"Identify exact matches between bloodmeal and human STR profiles — match_exact","text":"Match exact STR profiles bloodmeals humans. Note bloodmeal peak height threshold optional used filtering. Also note rm_twins = FALSE, match twin result multiple rows returned bloodmeal.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_exact.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify exact matches between bloodmeal and human STR profiles — match_exact","text":"","code":"match_exact(   bloodmeal_profiles,   human_profiles,   bloodmeal_ids = NULL,   human_ids = NULL,   peak_thresh = NULL,   rm_twins = TRUE,   rm_markers = NULL )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_exact.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify exact matches between bloodmeal and human STR profiles — match_exact","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL human_ids Vector human ids SampleName column human_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). rm_twins boolean indicating whether remove likely twins (identical STR profiles) human database prior identifying matches. Default: TRUE rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_exact.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify exact matches between bloodmeal and human STR profiles — match_exact","text":"Dataframe three columns: bloodmeal_id: bloodmeal ID human_id: human ID match (NA) match: whether match identified (yes )","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_exact.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Identify exact matches between bloodmeal and human STR profiles — match_exact","text":"","code":"match_exact(bloodmeal_profiles, human_profiles) #> # A tibble: 4 × 3 #>   bloodmeal_id human_id match #>                #> 1 evid1        NA       no    #> 2 evid2        NA       no    #> 3 evid3        NA       no    #> 4 evid4        NA       no"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_similarity.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify similarity matches between STR profiles from bloodmeals and a human\ndatabase — match_similarity","title":"Identify similarity matches between STR profiles from bloodmeals and a human\ndatabase — match_similarity","text":"Match STR profiles bloodmeals humans based threshold similar human-human pair. Twins included computing threshold. Note bloodmeal peak height threshold optional used filtering. Also note rm_twins = FALSE, match twin result multiple rows returned bloodmeal.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_similarity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify similarity matches between STR profiles from bloodmeals and a human\ndatabase — match_similarity","text":"","code":"match_similarity(   bloodmeal_profiles,   human_profiles,   bloodmeal_ids = NULL,   human_ids = NULL,   peak_thresh = NULL,   rm_twins = TRUE,   rm_markers = NULL,   return_similarities = FALSE )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_similarity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify similarity matches between STR profiles from bloodmeals and a human\ndatabase — match_similarity","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL human_ids Vector human ids SampleName column human_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). rm_twins boolean indicating whether remove likely twins (identical STR profiles) human database prior identifying matches. Default: TRUE rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations. return_similarities boolean indicating whether return human-human bloodmeal-human. Default: FALSE","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_similarity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify similarity matches between STR profiles from bloodmeals and a human\ndatabase — match_similarity","text":"Dataframe three columns: bloodmeal_id: bloodmeal ID human_id: human ID match (NA) match: whether match identified (yes ) similarity: similarity value match found return_similarities = TRUE, named list length 4 returned: matches: dataframe described max_hu_hu_similarity: maximum human-human similarity (threshold used matching) hu_hu_similarities: human-human similarity values, bm_hu_similarities: bloodmeal-human similarities profiles identical alleles least one marker","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_similarity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Identify similarity matches between STR profiles from bloodmeals and a human\ndatabase — match_similarity","text":"","code":"match_similarity(bloodmeal_profiles, human_profiles) #> Calculating human-human similarities #> Maximum similarity between people: 0.117647058823529 #> Calculating bloodmeal-human similarities #> Identifying matches #> # A tibble: 4 × 4 #>   bloodmeal_id human_id match similarity #>                      #> 1 evid1        P1       yes       0.294  #> 2 evid3        NA       no        0.0588 #> 3 evid2        NA       no       NA      #> 4 evid4        NA       no       NA"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_static_thresh.html","id":null,"dir":"Reference","previous_headings":"","what":"Match bloodmeals and humans based on log10LR static threshold — match_static_thresh","title":"Match bloodmeals and humans based on log10LR static threshold — match_static_thresh","text":"Match bloodmeals humans based log10LR static threshold","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_static_thresh.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Match bloodmeals and humans based on log10LR static threshold — match_static_thresh","text":"","code":"match_static_thresh(log10_lrs, thresh)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_static_thresh.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Match bloodmeals and humans based on log10LR static threshold — match_static_thresh","text":"log10_lrs Output calc_log10_lrs() bistro return_lrs = TRUE (lrs: second element list) thresh log10LR threshold matching. bloodmeal-human pairs log10LR ≥ thresh considered match.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_static_thresh.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Match bloodmeals and humans based on log10LR static threshold — match_static_thresh","text":"Dataframe including columns similar bistro() output.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_static_thresh.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Match bloodmeals and humans based on log10LR static threshold — match_static_thresh","text":"","code":"bistro_output <- bistro(bloodmeal_profiles, human_profiles,   pop_allele_freqs = pop_allele_freqs,   kit = \"ESX17\", peak_thresh = 200, return_lrs = TRUE ) #> 1/17 markers in kit but not in pop_allele_freqs: AMEL #> Formatting bloodmeal profiles #> Removing 6 peaks under the threshold of 200 RFU. #> For 1/4 bloodmeal ids, all peaks are below the threshold #> Formatting human profiles #> Markers being used: D10S1248, D12S391, D16S539, D18S51, D19S433, D1S1656, D21S11, D22S1045, D2S1338, D2S441, D3S1358, D8S1179, FGA, SE33, TH01, VWA #> Calculating log10LRs #> # bloodmeal ids: 3 #> # human ids: 3 #> Bloodmeal id 1/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Bloodmeal id 2/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Bloodmeal id 3/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Identifying matches match_static_thresh(bistro_output$lrs, 10) #> # A tibble: 4 × 6 #>   bloodmeal_id locus_count est_noc match human_id log10_lr #>                              #> 1 evid1                 16       2 yes   P1           21.8 #> 2 evid1                 16       2 yes   P2           10.3 #> 3 evid2                  1       2 no    NA           NA   #> 4 evid3                  8       1 no    NA           NA"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/pop_allele_freqs.html","id":null,"dir":"Reference","previous_headings":"","what":"Human population allele frequencies — pop_allele_freqs","title":"Human population allele frequencies — pop_allele_freqs","text":"Example population allele frequencies EuroForMix (ESX17_Norway)","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/pop_allele_freqs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Human population allele frequencies — pop_allele_freqs","text":"","code":"pop_allele_freqs"},{"path":[]},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/pop_allele_freqs.html","id":"pop-allele-freqs-a-data-frame-with-rows-and-columns-the","dir":"Reference","previous_headings":"","what":"pop_allele_freqs A data frame with 76 rows and 17 columns. The","title":"Human population allele frequencies — pop_allele_freqs","text":"first column STR allele following columns frequency allele different markers.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/pop_allele_freqs.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Human population allele frequencies — pop_allele_freqs","text":"http://euroformix.com/","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_bloodmeal_profiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Preprocess bloodmeal profiles — prep_bloodmeal_profiles","title":"Preprocess bloodmeal profiles — prep_bloodmeal_profiles","text":"Removes duplicates peaks threshold, subsets ids","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_bloodmeal_profiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Preprocess bloodmeal profiles — prep_bloodmeal_profiles","text":"","code":"prep_bloodmeal_profiles(   bloodmeal_profiles,   bloodmeal_ids = NULL,   peak_thresh = NULL,   rm_markers = c(\"AMEL\"),   check_heights = TRUE )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_bloodmeal_profiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Preprocess bloodmeal profiles — prep_bloodmeal_profiles","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations. check_heights boolean indicating whether check peak heights threshold. Default: TRUE","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_bloodmeal_profiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Preprocess bloodmeal profiles — prep_bloodmeal_profiles","text":"Dataframe preprocessed bloodmeal profiles","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_human_profiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Preprocess human profiles — prep_human_profiles","title":"Preprocess human profiles — prep_human_profiles","text":"Removes duplicates optionally twins, subsets ids","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_human_profiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Preprocess human profiles — prep_human_profiles","text":"","code":"prep_human_profiles(   human_profiles,   human_ids = NULL,   rm_twins = TRUE,   rm_markers = c(\"AMEL\") )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_human_profiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Preprocess human profiles — prep_human_profiles","text":"human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. human_ids Vector human ids SampleName column human_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL rm_twins boolean indicating whether remove likely twins (identical STR profiles) human database prior identifying matches. Default: TRUE rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_human_profiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Preprocess human profiles — prep_human_profiles","text":"Dataframe preprocessed human profiles","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_dups.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove duplicate rows with warning — rm_dups","title":"Remove duplicate rows with warning — rm_dups","text":"Remove duplicate rows warning","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_dups.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove duplicate rows with warning — rm_dups","text":"","code":"rm_dups(df)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_dups.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove duplicate rows with warning — rm_dups","text":"df Dataframe remove duplicate rows","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_dups.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove duplicate rows with warning — rm_dups","text":"Un-duplicated dataframe","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_markers.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove markers — rm_markers","title":"Remove markers — rm_markers","text":"Remove markers","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_markers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove markers — rm_markers","text":"","code":"rm_markers(profiles, markers)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_markers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove markers — rm_markers","text":"df Dataframe remove markers","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_markers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove markers — rm_markers","text":"Dataframe without markers","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_twins.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove identical STR profiles — rm_twins","title":"Remove identical STR profiles — rm_twins","text":"Remove identical STR profiles","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_twins.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove identical STR profiles — rm_twins","text":"","code":"rm_twins(human_profiles)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_twins.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove identical STR profiles — rm_twins","text":"human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_twins.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove identical STR profiles — rm_twins","text":"Data frame twins removed","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/subset_ids.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset to ids present in the dataset — subset_ids","title":"Subset to ids present in the dataset — subset_ids","text":"Subset ids present dataset","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/subset_ids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset to ids present in the dataset — subset_ids","text":"","code":"subset_ids(ids, vec, vec_name)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/subset_ids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subset to ids present in the dataset — subset_ids","text":"ids ids check vec vec vector ids vec_name name vector","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/subset_ids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subset to ids present in the dataset — subset_ids","text":"list IDs present","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/news/index.html","id":"bistro-011","dir":"Changelog","previous_headings":"","what":"bistro 0.1.1","title":"bistro 0.1.1","text":"Add DOI","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/news/index.html","id":"bistro-010","dir":"Changelog","previous_headings":"","what":"bistro 0.1.0","title":"bistro 0.1.0","text":"Initial package development. bistro() match_exact() match_similarity() match_static_thresh() Includes introductory vignette.","code":""}]
+[{"path":"https://duke-malaria-collaboratory.github.io/bistro/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2023 bistro authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"the-bistro-algorithm","dir":"Articles","previous_headings":"","what":"The bistro algorithm","title":"Introduction to using bistro","text":"bistro algorithm, R package, function within said R package. employs methods forensics identify matches bloodmeals people bit using short tandem repeat (STR) profiles human blood freshly fed bloodmeals people. can used match multi-source bloodmeals bloodmeals incomplete STR profiles. Note can use matching STR profiles research purposes, much recommend using forensic purposes. details algorithm, please refer bistro manuscript (add link ’s posted). core part algorithm contLikSearch() function euroformix package, used calculate log10 likelihood ratios (log10LRs). numerator log10LR likelihood person bitten vector denominator likelihood someone else bitten vector. information euroformix: - Manuscript: EuroForMix: open source software based continuous model evaluate STR DNA profiles mixture contributors artefacts - GitHub - Website explains GUI bistro uses log10LRs identify bloodmeal-human matches using per-bloodmeal dynamic threshold approach.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"installing-the-bistro-r-package","dir":"Articles","previous_headings":"","what":"Installing the bistro R package","title":"Introduction to using bistro","text":"install bistro, run following commands: run errors, try following: Windows: install Rtools Mac: install Xcode Mac App store","code":"install.packages(\"remotes\") # install remotes if needed remotes::install_github(\"duke-malaria-collaboratory/bistro\")"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"getting-started-with-bistro","dir":"Articles","previous_headings":"","what":"Getting started with bistro","title":"Introduction to using bistro","text":"important function bistro bistro(). document take required optional inputs, well output. summary, must provide: Bloodmeal STR profiles Human STR profiles STR genotyping kit name allele peak height threshold (relative fluorescence units, RFUs) bloodmeal STR profiles function outputs matches bloodmeal-human pair. follow along vignette, first load bistro: Note load bistro, also load euroformix bistro depends euroformix package.","code":"library(bistro) #> Loading required package: euroformix"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"required-inputs","dir":"Articles","previous_headings":"","what":"Required inputs","title":"Introduction to using bistro","text":"run bistro() using example data, let’s learn required inputs. Two required, one optional often recommended, datasets required run bistro(): bloodmeal human STR profiles required, human population allele frequencies optional. two required inputs STR genotyping kit name bloodmeal STR allele peak height threshold.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"bloodmeal-str-profiles-bloodmeal_profiles","dir":"Articles","previous_headings":"Required inputs","what":"Bloodmeal STR profiles (bloodmeal_profiles)","title":"Introduction to using bistro","text":"bloodmeal STR profiles dataset one row per allele bloodmeal marker, include allele peak height. Homozygous markers included (.e. one row). must four columns named SampleName, Marker, Allele, Height. SampleName column hold character values. example included bistro: example dataset, 4 different bloodmeals:","code":"head(bloodmeal_profiles) #>   SampleName   Marker Allele Height #> 1      evid1     AMEL      X   2136 #> 2      evid1     AMEL      Y   1015 #> 3      evid1 D10S1248     13   1856 #> 4      evid1 D10S1248     14    155 #> 5      evid1 D10S1248     15   1045 #> 6      evid1  D12S391     18    297 unique(bloodmeal_profiles$SampleName) #> [1] \"evid1\" \"evid2\" \"evid3\" \"evid4\""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"human-str-profiles-human_profiles","dir":"Articles","previous_headings":"Required inputs","what":"Human STR profiles (human_profiles)","title":"Introduction to using bistro","text":"human STR profiles dataset takes similar format bloodmeal STR profiles dataset - one row per allele human marker, require peak heights. , homozygous markers included . dataset must three columns named SampleName, Marker, Allele. SampleName column hold character values. example: example dataset, 3 different human profiles:","code":"head(human_profiles) #>                         SampleName   Marker Allele #> 1 00-JP0001-14_20142342311_NO-3241     AMEL      X #> 2 00-JP0001-14_20142342311_NO-3241     AMEL      Y #> 3 00-JP0001-14_20142342311_NO-3241 D10S1248     12 #> 4 00-JP0001-14_20142342311_NO-3241 D10S1248     13 #> 5 00-JP0001-14_20142342311_NO-3241  D12S391     17 #> 6 00-JP0001-14_20142342311_NO-3241  D12S391     18 unique(human_profiles$SampleName) #> [1] \"00-JP0001-14_20142342311_NO-3241\" \"P1\"                               #> [3] \"P2\""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"str-genotyping-kit-kit","dir":"Articles","previous_headings":"Required inputs","what":"STR genotyping kit (kit)","title":"Introduction to using bistro","text":"bistro requires input STR genotyping kit name. euroformix package includes kit parameters 23 common STR genotyping kits. also includes handy function list available kits: kit used genotype samples available defaults, modify kit.txt within euroformix package appropriate kit parameters. required parameters can usually found kit manufacturer’s documentation website.","code":"getKit() #>  [1] \"testkit\"       \"ESX16\"         \"ESX17\"         \"ESX17Fast\"     #>  [5] \"ESI17Fast\"     \"Fusion\"        \"Fusion 6C\"     \"SGMPlus\"       #>  [9] \"Identifiler\"   \"NGM\"           \"NGMSElect\"     \"NGMDetect\"     #> [13] \"GlobalFiler\"   \"PowerPlex16\"   \"PowerPlex21\"   \"24plex\"        #> [17] \"ESSPlex\"       \"ESSplexPlus\"   \"ESSplexSEPlus\" \"ESSplexSEQS\"   #> [21] \"ForenSeq\"      \"VFP\"           \"MiniFiler\""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"bloodmeal-allele-peak-threshold-peak_thresh","dir":"Articles","previous_headings":"Required inputs","what":"Bloodmeal allele peak threshold (peak_thresh)","title":"Introduction to using bistro","text":"bistro() also requires bloodmeal allele peak threshold (RFUs) provided. peaks heights threshold removed matching. prior filtering performed bloodmeal profiles based peak height, number equal greater threshold.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"human-population-allele-frequencies-pop_allele_freqs","dir":"Articles","previous_headings":"Required inputs","what":"Human population allele frequencies (pop_allele_freqs)","title":"Introduction to using bistro","text":"Human population frequencies allele locus may supplied. prefer, population allele frequencies can computed human STR profiles (see details). Note latter option suggested small set human reference profiles used. euroformix website provides publicly available population frequency datasets. Additionally, can get United States population allele frequencies many alleles NIST. like input population allele frequencies, dataset contain one column STR marker one row allele. alleles listed first column dataset column named “Allele”. entries marker-allele combination population allele frequency NA allele exist marker. example loci PowerPlex ESX 17 System (ESX17) kit.","code":"head(pop_allele_freqs) #>   Allele D3S1358        TH01 D21S11       D18S51 D10S1248 D1S1656 D2S1338 #> 1    5.0      NA 0.002598441     NA           NA       NA      NA      NA #> 2    6.0      NA 0.209274435     NA           NA       NA      NA      NA #> 3    6.3      NA          NA     NA           NA       NA      NA      NA #> 4    7.0      NA 0.212472516     NA 0.0008984726       NA      NA      NA #> 5    8.0      NA 0.083649810     NA           NA       NA      NA      NA #> 6    8.2      NA          NA     NA           NA       NA      NA      NA #>        D16S539 D22S1045 VWA    D8S1179 FGA D2S441 D12S391 D19S433        SE33 #> 1           NA       NA  NA         NA  NA     NA      NA      NA          NA #> 2 0.0008992806       NA  NA         NA  NA     NA      NA      NA          NA #> 3           NA       NA  NA         NA  NA     NA      NA      NA          NA #> 4           NA       NA  NA         NA  NA     NA      NA      NA          NA #> 5 0.0086930456       NA  NA 0.01130226  NA     NA      NA      NA          NA #> 6           NA       NA  NA         NA  NA     NA      NA      NA 0.002506945"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"running-bistro","dir":"Articles","previous_headings":"","what":"Running bistro()","title":"Introduction to using bistro","text":"Now enough background run bistro(), let’s test using example data included package: ’ll notice bunch messages print screen: One markers (AMEL) kit pop_allele_freqs. 6 peaks 200 RFU threshold removed, filtering one bloodmeals peaks remaining threshold. Notification log10LRs (log10 likelihood ratios) calculated bloodmeal-human pair (4 bloodmeals 3 humans). can take , progress also printed . Notification matches identified. Let’s take look output: output contains 8 columns: bloodmeal_id: bloodmeal sample name. est_noc: estimated number contributors (NOCs) bloodmeal. equals one, ’s predicted single-source bloodmeal; greater one, ’s predicted multi-source bloodmeal. Note sources mean humans . locus_count: number loci STR-typed bloodmeal. match: whether bloodmeal STR profile matched human database (yes ). human_id: human match bloodmeal (NA match). log10_lr: log10 likelihood ratio bloodmeal-human match (NA match). numerator log10LR likelihood person bitten bloodmeal denominator likelihood someone else bitten bloodmeal. notes: bloodmeal doesn’t match (see details). thresh_low: log10LR threshold match made. important thing notice , even though 4 bloodmeals, 5 rows output dataset. , bloodmeal appear least dataset, multiple rows present bloodmeals match multiple people (one row per match). example, , evid1 matches 2 different people (P1 P2) Please keep mind performing data analysis. notes column provides information match: passed filters: match. > min NOC matches: matches expected resolved. can happen closely related people human reference dataset. shared alleles: people human reference dataset alleles overlapped alleles bloodmeal. log10LRs < 1.5: none log10LRs high enough considered match. euroformix error: euroformix::contLikSearch() function run successfully. often happens incomplete bloodmeal profiles (.e. markers succesfully STR-typed). peaks threshold: bloodmeal STR peaks peak height threshold. timed : log-likelihood took long calculate. want give time, can modify time_limit argument (see ).","code":"bistro_output <- bistro(   bloodmeal_profiles = bloodmeal_profiles,   human_profiles = human_profiles,   pop_allele_freqs = pop_allele_freqs,   kit = \"ESX17\",   peak_thresh = 200 ) #> 1/17 markers in kit but not in pop_allele_freqs: AMEL #> Formatting bloodmeal profiles #> Removing 6 peaks under the threshold of 200 RFU. #> For 1/4 bloodmeal ids, all peaks are below the threshold #> Formatting human profiles #> Markers being used: D10S1248, D12S391, D16S539, D18S51, D19S433, D1S1656, D21S11, D22S1045, D2S1338, D2S441, D3S1358, D8S1179, FGA, SE33, TH01, VWA #> Calculating log10LRs #> # bloodmeal ids: 3 #> # human ids: 3 #> Bloodmeal id 1/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Bloodmeal id 2/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Bloodmeal id 3/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Identifying matches bistro_output #> # A tibble: 4 × 8 #>   bloodmeal_id locus_count est_noc match human_id log10_lr notes      thresh_low #>                                          #> 1 evid1                 16       2 yes   P1           21.8 passed al…        9.5 #> 2 evid1                 16       2 yes   P2           10.3 passed al…        9.5 #> 3 evid2                  1       2 no    NA           NA   all log10…       NA   #> 4 evid3                  8       1 no    NA           NA   all log10…       NA"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"using-computed-population-allele-frequencies","dir":"Articles","previous_headings":"","what":"Using computed population allele frequencies","title":"Introduction to using bistro","text":"want population allele frequencies computed inputted human reference profiles, must set calc_allele_freqs = TRUE: Note , use builtin dataset example , recommend using method human dataset 3 people. example may make sense relatively comprehensive set human reference profiles study site.","code":"bistro(   bloodmeal_profiles = bloodmeal_profiles,   human_profiles = human_profiles,   calc_allele_freqs = TRUE,   kit = \"ESX17\",   peak_thresh = 200 )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"running-bistro-on-a-subset-of-samples","dir":"Articles","previous_headings":"","what":"Running bistro() on a subset of samples","title":"Introduction to using bistro","text":"bistro() can take long time run, especially many samples closely related reference population. Therefore, running samples, highly recommend testing small subset samples make sure everything working expect. , can use bloodmeal_ids human_ids arguments tell bistro() ids want compare: can also useful like parallelize bistro(), example using workflow manager Snakemake NextFlow. ’d like try , template Snakemake pipeline running bistro. highly recommend planning run many samples.","code":"bistro(   bloodmeal_profiles = bloodmeal_profiles,   human_profiles = human_profiles,   pop_allele_freqs = pop_allele_freqs,   kit = \"ESX17\",   peak_thresh = 200,   bloodmeal_ids = c(\"evid1\", \"evid2\"),   human_ids = \"P1\" )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"other-arguments","dir":"Articles","previous_headings":"","what":"Other arguments","title":"Introduction to using bistro","text":"arguments can modify running bistro() include: Used bistro: rm_twins: whether remove identical STR profiles likely twins prior identifying matches. Note matches people resolved (default: TRUE) time_limit: longest amount time allowed calculate log-likelihood one bloodmeal-human pair, minutes (default: 3) Used euroformix::contLikSearch() calculating log-likelihoods: rm_markers: markers use calculating LRs. default, AMEL removed standard use calculating LRs sex-specific marker model_degrad: whether model peak degradation (default: TRUE) model_bw_stutt model_fw_stutt: whether model peak backward forward stutter (default: FALSE) difftol: difference tolerance log-likelihood across 2 iterations (default: 1) threads: number threads use computing log-likelihoods (default: 4) seed: seed reproducible results (default: 1) return_lr: whether return bloodmeal-human log10LRs. useful want investigate matches perform static threshold matching (see ) (default: FALSE)","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/articles/bistro.html","id":"other-matching-algorithms","dir":"Articles","previous_headings":"","what":"Other matching algorithms","title":"Introduction to using bistro","text":"also implemented matching algorithms including: match_exact(): Exact matching markers alleles match_similarity(): Similarity matching based highest similarity value humans reference database match_static_threshold(): Matching based static log10LR threshold. algorithms take similar inputs bistro(), case match_static_threshold(), bistro() output. Look upcoming manuscript comparison methods.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Zena Lapp. Author, maintainer. Christine Markwalter. Author.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Lapp Z, Markwalter C (2023). bistro: Bloodmeal identification STR overlap. https://duke-malaria-collaboratory.github.io/bistro/, https://github.com/duke-malaria-collaboratory/bistro.","code":"@Manual{,   title = {bistro: Bloodmeal identification by STR overlap},   author = {Zena Lapp and Christine Markwalter},   year = {2023},   note = {https://duke-malaria-collaboratory.github.io/bistro/, https://github.com/duke-malaria-collaboratory/bistro}, }"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/index.html","id":"bistro-bloodmeal-identification-by-str-overlap-","dir":"","previous_headings":"","what":"Bloodmeal identification by STR overlap","title":"Bloodmeal identification by STR overlap","text":"Functions allow identification matches bloodmeals people bit using short tandem repeat (STR) profiles human blood freshly fed bloodmeals people.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Bloodmeal identification by STR overlap","text":"can install bistro like :","code":"# install.packages(\"remotes\") remotes::install_github(\"duke-malaria-collaboratory/bistro\")"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/index.html","id":"dependencies","dir":"","previous_headings":"","what":"Dependencies:","title":"Bloodmeal identification by STR overlap","text":"Depends: R (>= 4.0.0), euroformix (>= 4.0.7) Imports: codetools (>= 0.2.19), dplyr (>= 1.1.3), R.utils (>= 2.12.2), stringr (>= 1.5.0), tibble (>= 3.2.1), tidyr (>= 1.3.0) Suggests: knitr (>= 1.43), readr (>= 2.1.4), rmarkdown (>= 2.24), testthat (>= 3.0.0)","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Bloodmeal identification by STR overlap","text":"Check vignette information.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bistro.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify human contributors to a bloodmeal using STR profiles — bistro","title":"Identify human contributors to a bloodmeal using STR profiles — bistro","text":"Identifies matches bloodmeal STR profiles database human STR profiles. euroformix::contLikSearch() function used calculate log10 likelihood ratios (log10_lrs) used identify human contributors bloodmeal. details present , see vignette('bistro').","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bistro.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify human contributors to a bloodmeal using STR profiles — bistro","text":"","code":"bistro(   bloodmeal_profiles,   human_profiles,   kit,   peak_thresh,   pop_allele_freqs = NULL,   calc_allele_freqs = FALSE,   bloodmeal_ids = NULL,   human_ids = NULL,   rm_twins = TRUE,   rm_markers = c(\"AMEL\"),   model_degrad = TRUE,   model_bw_stutt = FALSE,   model_fw_stutt = FALSE,   difftol = 1,   threads = 4,   seed = 1,   time_limit = 3,   return_lrs = FALSE )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bistro.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify human contributors to a bloodmeal using STR profiles — bistro","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. kit STR kit name euroformix. see list kits embedded euroformix use euroformix::getKit(). kit included, see vignette(\"bistro\") details include kit. peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). pop_allele_freqs Data frame first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA. NULL calc_allele_freqs = TRUE, population allele frequencies calculated human_profiles. calc_allele_freqs boolean indicating whether calculate allele frequencies human_profiles. FALSE, pop_allele_freqs input required. Default: FALSE bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL human_ids Vector human ids SampleName column human_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL rm_twins boolean indicating whether remove likely twins (identical STR profiles) human database prior identifying matches. Default: TRUE rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations. model_degrad boolean indicating whether model peak degradation. Used modelDegrad argument euroformix::contLikSearch(). Default: TRUE model_bw_stutt boolean indicating whether model peak backward stutter. Used modelBWstutt argument euroformix::contLikSearch(). Default: FALSE model_fw_stutt boolean indicating whether model peak forward stutter. Used modelFWstutt argument euroformix::contLikSearch(). Default: FALSE difftol Tolerance difference log likelihoods across 2 iterations. euroformix::contLikSearch() argument. Default: 1 threads Number threads use calculating log10_lrs. euroformix::contLikSearch() argument. Default: 4 seed Seed calculating log10_lrs. euroformix::contLikSearch() argument. Default: 1 time_limit Time limit minutes run euroformix::contLikSearch() function 1 bloodmeal-human pair. Default: 3 return_lrs boolean indicating whether return log10LRs bloodmeal-human pairs. Default: FALSE","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bistro.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify human contributors to a bloodmeal using STR profiles — bistro","text":"Tibble matches bloodmeal-human pairs including columns listed . Note multiple matches found bloodmeal, included separate rows. bloodmeal_id: bloodmeal id locus_count: number loci successfully typed bloodmeal est_noc: estimated number contributors bloodmeal match: whether match identified given bloodmeal (yes ) human_id: match, human id (NA otherwise) log10_lr: match, log10 likelihood ratio (NA otherwise) notes: bloodmeal match return_lrs = TRUE, named list length 2 returned: matches - tibble described lrs - log10LRs bloodmeal-human pair including columns described additional column: efm_noc, number contributors used input euroformix, min(est_noc, 3).","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bistro.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Identify human contributors to a bloodmeal using STR profiles — bistro","text":"","code":"bistro(bloodmeal_profiles, human_profiles,   pop_allele_freqs = pop_allele_freqs,   kit = \"ESX17\", peak_thresh = 200 ) #> 1/17 markers in kit but not in pop_allele_freqs: AMEL #> Formatting bloodmeal profiles #> Removing 6 peaks under the threshold of 200 RFU. #> For 1/4 bloodmeal ids, all peaks are below the threshold #> Formatting human profiles #> Markers being used: D10S1248, D12S391, D16S539, D18S51, D19S433, D1S1656, D21S11, D22S1045, D2S1338, D2S441, D3S1358, D8S1179, FGA, SE33, TH01, VWA #> Calculating log10LRs #> # bloodmeal ids: 3 #> # human ids: 3 #> Bloodmeal id 1/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Bloodmeal id 2/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Bloodmeal id 3/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Identifying matches #> # A tibble: 4 × 8 #>   bloodmeal_id locus_count est_noc match human_id log10_lr notes      thresh_low #>                                          #> 1 evid1                 16       2 yes   P1           21.8 passed al…        9.5 #> 2 evid1                 16       2 yes   P2           10.3 passed al…        9.5 #> 3 evid2                  1       2 no    NA           NA   all log10…       NA   #> 4 evid3                  8       1 no    NA           NA   all log10…       NA"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bloodmeal_profiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Bloodmeal STR profiles — bloodmeal_profiles","title":"Bloodmeal STR profiles — bloodmeal_profiles","text":"Example \"bloodmeal\" STR profiles EuroForMix","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bloodmeal_profiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bloodmeal STR profiles — bloodmeal_profiles","text":"","code":"bloodmeal_profiles"},{"path":[]},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bloodmeal_profiles.html","id":"bloodmeal-profiles","dir":"Reference","previous_headings":"","what":"bloodmeal_profiles","title":"Bloodmeal STR profiles — bloodmeal_profiles","text":"data frame 69 rows 4 columns: SampleName Human sample identifier Marker STR marker Allele STR allele Height STR peak height","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/bloodmeal_profiles.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Bloodmeal STR profiles — bloodmeal_profiles","text":"http://euroformix.com/","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_allele_freqs.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate allele frequencies — calc_allele_freqs","title":"Calculate allele frequencies — calc_allele_freqs","text":"Calculate allele frequencies (generally human) population.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_allele_freqs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate allele frequencies — calc_allele_freqs","text":"","code":"calc_allele_freqs(human_profiles, rm_markers = NULL)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_allele_freqs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate allele frequencies — calc_allele_freqs","text":"human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_allele_freqs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate allele frequencies — calc_allele_freqs","text":"tibble first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_log10_lrs.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate log10_lrs for multiple bloodmeal-human pairs — calc_log10_lrs","title":"Calculate log10_lrs for multiple bloodmeal-human pairs — calc_log10_lrs","text":"Note function preprocess bloodmeal human profile data. like preprocess way performed internally bistro() function, must run prep_bloodmeal_profiles() prep_human_profiles() first.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_log10_lrs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate log10_lrs for multiple bloodmeal-human pairs — calc_log10_lrs","text":"","code":"calc_log10_lrs(   bloodmeal_profiles,   human_profiles,   pop_allele_freqs,   kit,   peak_thresh,   bloodmeal_ids = NULL,   human_ids = NULL,   model_degrad = TRUE,   model_bw_stutt = FALSE,   model_fw_stutt = FALSE,   difftol = 1,   threads = 4,   seed = 1,   time_limit = 3 )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_log10_lrs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate log10_lrs for multiple bloodmeal-human pairs — calc_log10_lrs","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. pop_allele_freqs Data frame first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA. NULL calc_allele_freqs = TRUE, population allele frequencies calculated human_profiles. kit STR kit name euroformix. see list kits embedded euroformix use euroformix::getKit(). kit included, see vignette(\"bistro\") details include kit. peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL human_ids Vector human ids SampleName column human_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL model_degrad boolean indicating whether model peak degradation. Used modelDegrad argument euroformix::contLikSearch(). Default: TRUE model_bw_stutt boolean indicating whether model peak backward stutter. Used modelBWstutt argument euroformix::contLikSearch(). Default: FALSE model_fw_stutt boolean indicating whether model peak forward stutter. Used modelFWstutt argument euroformix::contLikSearch(). Default: FALSE difftol Tolerance difference log likelihoods across 2 iterations. euroformix::contLikSearch() argument. Default: 1 threads Number threads use calculating log10_lrs. euroformix::contLikSearch() argument. Default: 4 seed Seed calculating log10_lrs. euroformix::contLikSearch() argument. Default: 1 time_limit Time limit minutes run euroformix::contLikSearch() function 1 bloodmeal-human pair. Default: 3","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_log10_lrs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate log10_lrs for multiple bloodmeal-human pairs — calc_log10_lrs","text":"tibble output bistro(), except match column every bloodmeal-human pair calculated log10_lr included. additional column efm_noc number contributors used euroformix::contLikSearch(). maximum value 3.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_one_log10_lr.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate log10_lr for one bloodmeal-human pair — calc_one_log10_lr","title":"Calculate log10_lr for one bloodmeal-human pair — calc_one_log10_lr","text":"Calculate log10_lr one bloodmeal-human pair","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_one_log10_lr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate log10_lr for one bloodmeal-human pair — calc_one_log10_lr","text":"","code":"calc_one_log10_lr(   bloodmeal_profiles,   bloodmeal_id,   human_profiles,   human_id,   pop_allele_freqs,   kit,   peak_thresh,   model_degrad = TRUE,   model_bw_stutt = FALSE,   model_fw_stutt = FALSE,   difftol = 1,   threads = 4,   seed = 1,   time_limit = 3 )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_one_log10_lr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate log10_lr for one bloodmeal-human pair — calc_one_log10_lr","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. bloodmeal_id Bloodmeal id SampleName column bloodmeal_profiles compute log10_lr human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. human_id Human id SampleName column human_profiles compute log10_lr pop_allele_freqs Data frame first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA. NULL calc_allele_freqs = TRUE, population allele frequencies calculated human_profiles. kit STR kit name euroformix. see list kits embedded euroformix use euroformix::getKit(). kit included, see vignette(\"bistro\") details include kit. peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). model_degrad boolean indicating whether model peak degradation. Used modelDegrad argument euroformix::contLikSearch(). Default: TRUE model_bw_stutt boolean indicating whether model peak backward stutter. Used modelBWstutt argument euroformix::contLikSearch(). Default: FALSE model_fw_stutt boolean indicating whether model peak forward stutter. Used modelFWstutt argument euroformix::contLikSearch(). Default: FALSE difftol Tolerance difference log likelihoods across 2 iterations. euroformix::contLikSearch() argument. Default: 1 threads Number threads use calculating log10_lrs. euroformix::contLikSearch() argument. Default: 4 seed Seed calculating log10_lrs. euroformix::contLikSearch() argument. Default: 1 time_limit Time limit minutes run euroformix::contLikSearch() function 1 bloodmeal-human pair. Default: 3","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/calc_one_log10_lr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate log10_lr for one bloodmeal-human pair — calc_one_log10_lr","text":"tibble log10_lr bloodmeal-human pair including bloodmeal_id, human_id, locus_count (number STR loci used matching), est_noc (estimated number contributors), efm_noc (number contributors used euroformix), log10_lr (log10 likelihood ratio), notes","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_bistro_inputs.html","id":null,"dir":"Reference","previous_headings":"","what":"Check bistro inputs — check_bistro_inputs","title":"Check bistro inputs — check_bistro_inputs","text":"Check bistro inputs","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_bistro_inputs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check bistro inputs — check_bistro_inputs","text":"","code":"check_bistro_inputs(   bloodmeal_profiles,   human_profiles,   kit,   peak_thresh,   pop_allele_freqs,   calc_allele_freqs,   bloodmeal_ids,   human_ids,   rm_twins,   rm_markers,   model_degrad,   model_bw_stutt,   model_fw_stutt,   difftol,   threads,   seed,   time_limit,   return_lrs )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_bistro_inputs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check bistro inputs — check_bistro_inputs","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. kit STR kit name euroformix. see list kits embedded euroformix use euroformix::getKit(). kit included, see vignette(\"bistro\") details include kit. peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). pop_allele_freqs Data frame first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA. NULL calc_allele_freqs = TRUE, population allele frequencies calculated human_profiles. calc_allele_freqs boolean indicating whether calculate allele frequencies human_profiles. FALSE, pop_allele_freqs input required. Default: FALSE bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL human_ids Vector human ids SampleName column human_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL rm_twins boolean indicating whether remove likely twins (identical STR profiles) human database prior identifying matches. Default: TRUE rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations. model_degrad boolean indicating whether model peak degradation. Used modelDegrad argument euroformix::contLikSearch(). Default: TRUE model_bw_stutt boolean indicating whether model peak backward stutter. Used modelBWstutt argument euroformix::contLikSearch(). Default: FALSE model_fw_stutt boolean indicating whether model peak forward stutter. Used modelFWstutt argument euroformix::contLikSearch(). Default: FALSE difftol Tolerance difference log likelihoods across 2 iterations. euroformix::contLikSearch() argument. Default: 1 threads Number threads use calculating log10_lrs. euroformix::contLikSearch() argument. Default: 4 seed Seed calculating log10_lrs. euroformix::contLikSearch() argument. Default: 1 time_limit Time limit minutes run euroformix::contLikSearch() function 1 bloodmeal-human pair. Default: 3 return_lrs boolean indicating whether return log10LRs bloodmeal-human pairs. Default: FALSE","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_bistro_inputs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check bistro inputs — check_bistro_inputs","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_calc_allele_freqs.html","id":null,"dir":"Reference","previous_headings":"","what":"Check calc_allele_freqs — check_calc_allele_freqs","title":"Check calc_allele_freqs — check_calc_allele_freqs","text":"Check calc_allele_freqs","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_calc_allele_freqs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check calc_allele_freqs — check_calc_allele_freqs","text":"","code":"check_calc_allele_freqs(calc_allele_freqs)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_calc_allele_freqs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check calc_allele_freqs — check_calc_allele_freqs","text":"calc_allele_freqs boolean indicating whether calculate allele frequencies human_profiles. FALSE, pop_allele_freqs input required. Default: FALSE","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_calc_allele_freqs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check calc_allele_freqs — check_calc_allele_freqs","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_colnames.html","id":null,"dir":"Reference","previous_headings":"","what":"Check column names — check_colnames","title":"Check column names — check_colnames","text":"Check column names","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_colnames.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check column names — check_colnames","text":"","code":"check_colnames(df, expected_colnames)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_colnames.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check column names — check_colnames","text":"df Dataframe check expected_colnames Column names required resent","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_colnames.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check column names — check_colnames","text":"Nothing error","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_heights.html","id":null,"dir":"Reference","previous_headings":"","what":"Check peak_thresh — check_heights","title":"Check peak_thresh — check_heights","text":"Check peak_thresh","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_heights.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check peak_thresh — check_heights","text":"","code":"check_heights(heights, peak_thresh)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_heights.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check peak_thresh — check_heights","text":"heights vector peak heights peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch().","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_heights.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check peak_thresh — check_heights","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_ids.html","id":null,"dir":"Reference","previous_headings":"","what":"Check input ids — check_ids","title":"Check input ids — check_ids","text":"Check input ids","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_ids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check input ids — check_ids","text":"","code":"check_ids(vec, vec_name)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_ids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check input ids — check_ids","text":"vec vector check vec_name vector name","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_ids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check input ids — check_ids","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_if_allele_freqs.html","id":null,"dir":"Reference","previous_headings":"","what":"Check calc_if_allele_freqs — check_if_allele_freqs","title":"Check calc_if_allele_freqs — check_if_allele_freqs","text":"Check calc_if_allele_freqs","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_if_allele_freqs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check calc_if_allele_freqs — check_if_allele_freqs","text":"","code":"check_if_allele_freqs(pop_allele_freqs, calc_allele_freqs, kit_df)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_if_allele_freqs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check calc_if_allele_freqs — check_if_allele_freqs","text":"pop_allele_freqs Data frame first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA. NULL calc_allele_freqs = TRUE, population allele frequencies calculated human_profiles. calc_allele_freqs boolean indicating whether calculate allele frequencies human_profiles. FALSE, pop_allele_freqs input required. Default: FALSE kit_df Kit dataframe euroformix::getKit()","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_if_allele_freqs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check calc_if_allele_freqs — check_if_allele_freqs","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_bool.html","id":null,"dir":"Reference","previous_headings":"","what":"Check is boolean — check_is_bool","title":"Check is boolean — check_is_bool","text":"Check boolean","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_bool.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check is boolean — check_is_bool","text":"","code":"check_is_bool(vec, vec_name)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_bool.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check is boolean — check_is_bool","text":"vec vector check vec_name vector name","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_bool.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check is boolean — check_is_bool","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_numeric.html","id":null,"dir":"Reference","previous_headings":"","what":"Check is numeric — check_is_numeric","title":"Check is numeric — check_is_numeric","text":"Check numeric","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_numeric.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check is numeric — check_is_numeric","text":"","code":"check_is_numeric(vec, vec_name, pos = FALSE)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_numeric.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check is numeric — check_is_numeric","text":"vec vector check vec_name vector name pos whether number must positive","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_is_numeric.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check is numeric — check_is_numeric","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_kit.html","id":null,"dir":"Reference","previous_headings":"","what":"Check kit — check_kit","title":"Check kit — check_kit","text":"Check kit","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_kit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check kit — check_kit","text":"","code":"check_kit(kit)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_kit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check kit — check_kit","text":"kit STR kit name euroformix. see list kits embedded euroformix use euroformix::getKit(). kit included, see vignette(\"bistro\") details include kit.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_kit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check kit — check_kit","text":"Error kit exist, dataframe kit otherwise","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_peak_thresh.html","id":null,"dir":"Reference","previous_headings":"","what":"Check peak_thresh — check_peak_thresh","title":"Check peak_thresh — check_peak_thresh","text":"Check peak_thresh","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_peak_thresh.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check peak_thresh — check_peak_thresh","text":"","code":"check_peak_thresh(peak_thresh)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_peak_thresh.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check peak_thresh — check_peak_thresh","text":"peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch().","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_peak_thresh.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check peak_thresh — check_peak_thresh","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_setdiff_markers.html","id":null,"dir":"Reference","previous_headings":"","what":"Check what markers are present — check_setdiff_markers","title":"Check what markers are present — check_setdiff_markers","text":"Check markers present","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_setdiff_markers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check what markers are present — check_setdiff_markers","text":"","code":"check_setdiff_markers(markers1, markers2, markers1_name, markers2_name)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_setdiff_markers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check what markers are present — check_setdiff_markers","text":"markers1 first vector check markers2 second vector check markers1_name first vector name markers2_name second vector name","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/check_setdiff_markers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check what markers are present — check_setdiff_markers","text":"Error nothing","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/filter_peaks.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter peak heights that are under threshold — filter_peaks","title":"Filter peak heights that are under threshold — filter_peaks","text":"Filter peak heights threshold","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/filter_peaks.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter peak heights that are under threshold — filter_peaks","text":"","code":"filter_peaks(bloodmeal_profiles, peak_thresh)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/filter_peaks.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter peak heights that are under threshold — filter_peaks","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch().","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/filter_peaks.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter peak heights that are under threshold — filter_peaks","text":"Filtered dataframe","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_allele_freqs.html","id":null,"dir":"Reference","previous_headings":"","what":"Format population allele frequencies — format_allele_freqs","title":"Format population allele frequencies — format_allele_freqs","text":"Format population allele frequencies input euroformix contLikSearch() function.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_allele_freqs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format population allele frequencies — format_allele_freqs","text":"","code":"format_allele_freqs(pop_allele_freqs)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_allele_freqs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format population allele frequencies — format_allele_freqs","text":"pop_allele_freqs Data frame first column STR allele following columns frequency allele different markers. Alleles exist given marker coded NA. NULL calc_allele_freqs = TRUE, population allele frequencies calculated human_profiles.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_allele_freqs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format population allele frequencies — format_allele_freqs","text":"list allele frequencies population format required input euroformix contLikSearch() function","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_bloodmeal_profiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Format bloodmeal STR profiles — format_bloodmeal_profiles","title":"Format bloodmeal STR profiles — format_bloodmeal_profiles","text":"Format bloodmeal STR profiles input euroformix contLikSearch() function.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_bloodmeal_profiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format bloodmeal STR profiles — format_bloodmeal_profiles","text":"","code":"format_bloodmeal_profiles(bloodmeal_profiles)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_bloodmeal_profiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format bloodmeal STR profiles — format_bloodmeal_profiles","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_bloodmeal_profiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format bloodmeal STR profiles — format_bloodmeal_profiles","text":"list lists including alleles sample format required input euroformix contLikSearch() function.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_human_profiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Format human STR profiles — format_human_profiles","title":"Format human STR profiles — format_human_profiles","text":"Format human STR profiles input euroformix contLikSearch() function.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_human_profiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format human STR profiles — format_human_profiles","text":"","code":"format_human_profiles(human_profiles)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_human_profiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format human STR profiles — format_human_profiles","text":"human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/format_human_profiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format human STR profiles — format_human_profiles","text":"list lists including alleles sample format required input euroformix contLikSearch() function","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_bloodmeal_human_similarity.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify matches between bloodmeal and human STR profiles\nbased on similarity values — get_bloodmeal_human_similarity","title":"Identify matches between bloodmeal and human STR profiles\nbased on similarity values — get_bloodmeal_human_similarity","text":"Identify matches bloodmeal human STR profiles based similarity values","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_bloodmeal_human_similarity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify matches between bloodmeal and human STR profiles\nbased on similarity values — get_bloodmeal_human_similarity","text":"","code":"get_bloodmeal_human_similarity(bloodmeal_profiles, human_profiles)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_bloodmeal_human_similarity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify matches between bloodmeal and human STR profiles\nbased on similarity values — get_bloodmeal_human_similarity","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_bloodmeal_human_similarity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify matches between bloodmeal and human STR profiles\nbased on similarity values — get_bloodmeal_human_similarity","text":"dataframe two columns: bloodmeal_id: bloodmeal ID human_id: human ID match, \"match\" match","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_human_similarity.html","id":null,"dir":"Reference","previous_headings":"","what":"Get pairwise human STR profile similarities — get_human_similarity","title":"Get pairwise human STR profile similarities — get_human_similarity","text":"Get pairwise human STR profile similarities","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_human_similarity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get pairwise human STR profile similarities — get_human_similarity","text":"","code":"get_human_similarity(human_profiles)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_human_similarity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get pairwise human STR profile similarities — get_human_similarity","text":"human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/get_human_similarity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get pairwise human STR profile similarities — get_human_similarity","text":"Dataframe three columns: hu1: human ID 1 hu2: human ID 2 similarity: similarity value (# exact locus matches / # loci)","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/human_profiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Human reference database — human_profiles","title":"Human reference database — human_profiles","text":"Example human STR profiles EuroForMix","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/human_profiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Human reference database — human_profiles","text":"","code":"human_profiles"},{"path":[]},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/human_profiles.html","id":"human-profiles","dir":"Reference","previous_headings":"","what":"human_profiles","title":"Human reference database — human_profiles","text":"data frame 96 rows 3 columns: SampleName Human sample identifier Marker STR marker Allele STR allele","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/human_profiles.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Human reference database — human_profiles","text":"http://euroformix.com/","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_matches.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify matches for multiple bloodmeal-human pairs — identify_matches","title":"Identify matches for multiple bloodmeal-human pairs — identify_matches","text":"Identify matches multiple bloodmeal-human pairs","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_matches.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify matches for multiple bloodmeal-human pairs — identify_matches","text":"","code":"identify_matches(log10_lrs, bloodmeal_ids = NULL)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_matches.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify matches for multiple bloodmeal-human pairs — identify_matches","text":"log10_lrs Output calc_log10_lrs() bistro return_lrs = TRUE (lrs: second element list) bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_matches.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify matches for multiple bloodmeal-human pairs — identify_matches","text":"tibble output bistro().","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_one_match_set.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify matches between a bloodmeal and human references — identify_one_match_set","title":"Identify matches between a bloodmeal and human references — identify_one_match_set","text":"Identify matches bloodmeal human references","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_one_match_set.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify matches between a bloodmeal and human references — identify_one_match_set","text":"","code":"identify_one_match_set(log10_lrs, bloodmeal_id)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_one_match_set.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify matches between a bloodmeal and human references — identify_one_match_set","text":"log10_lrs output calc_log10_lrs() bloodmeal_id Bloodmeal id SampleName column bloodmeal_profiles compute log10_lr","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/identify_one_match_set.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify matches between a bloodmeal and human references — identify_one_match_set","text":"tibble matches bloodmeal-human pairs including bloodmeal_id, locus_count (number STR loci used matching), est_noc (estimated number contributors), match, human_id (match), log10_lr (log10 likelihood ratio), notes","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_exact.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify exact matches between bloodmeal and human STR profiles — match_exact","title":"Identify exact matches between bloodmeal and human STR profiles — match_exact","text":"Match exact STR profiles bloodmeals humans. Note bloodmeal peak height threshold optional used filtering. Also note rm_twins = FALSE, match twin result multiple rows returned bloodmeal.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_exact.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify exact matches between bloodmeal and human STR profiles — match_exact","text":"","code":"match_exact(   bloodmeal_profiles,   human_profiles,   bloodmeal_ids = NULL,   human_ids = NULL,   peak_thresh = NULL,   rm_twins = TRUE,   rm_markers = NULL )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_exact.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify exact matches between bloodmeal and human STR profiles — match_exact","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL human_ids Vector human ids SampleName column human_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). rm_twins boolean indicating whether remove likely twins (identical STR profiles) human database prior identifying matches. Default: TRUE rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_exact.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify exact matches between bloodmeal and human STR profiles — match_exact","text":"Dataframe three columns: bloodmeal_id: bloodmeal ID human_id: human ID match (NA) match: whether match identified (yes )","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_exact.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Identify exact matches between bloodmeal and human STR profiles — match_exact","text":"","code":"match_exact(bloodmeal_profiles, human_profiles) #> # A tibble: 4 × 3 #>   bloodmeal_id human_id match #>                #> 1 evid1        NA       no    #> 2 evid2        NA       no    #> 3 evid3        NA       no    #> 4 evid4        NA       no"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_similarity.html","id":null,"dir":"Reference","previous_headings":"","what":"Identify similarity matches between STR profiles from bloodmeals and a human\ndatabase — match_similarity","title":"Identify similarity matches between STR profiles from bloodmeals and a human\ndatabase — match_similarity","text":"Match STR profiles bloodmeals humans based threshold similar human-human pair. Twins included computing threshold. Note bloodmeal peak height threshold optional used filtering. Also note rm_twins = FALSE, match twin result multiple rows returned bloodmeal.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_similarity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Identify similarity matches between STR profiles from bloodmeals and a human\ndatabase — match_similarity","text":"","code":"match_similarity(   bloodmeal_profiles,   human_profiles,   bloodmeal_ids = NULL,   human_ids = NULL,   peak_thresh = NULL,   rm_twins = TRUE,   rm_markers = NULL,   return_similarities = FALSE )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_similarity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Identify similarity matches between STR profiles from bloodmeals and a human\ndatabase — match_similarity","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL human_ids Vector human ids SampleName column human_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). rm_twins boolean indicating whether remove likely twins (identical STR profiles) human database prior identifying matches. Default: TRUE rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations. return_similarities boolean indicating whether return human-human bloodmeal-human. Default: FALSE","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_similarity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Identify similarity matches between STR profiles from bloodmeals and a human\ndatabase — match_similarity","text":"Dataframe three columns: bloodmeal_id: bloodmeal ID human_id: human ID match (NA) match: whether match identified (yes ) similarity: similarity value match found return_similarities = TRUE, named list length 4 returned: matches: dataframe described max_hu_hu_similarity: maximum human-human similarity (threshold used matching) hu_hu_similarities: human-human similarity values, bm_hu_similarities: bloodmeal-human similarities profiles identical alleles least one marker","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_similarity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Identify similarity matches between STR profiles from bloodmeals and a human\ndatabase — match_similarity","text":"","code":"match_similarity(bloodmeal_profiles, human_profiles) #> Calculating human-human similarities #> Maximum similarity between people: 0.117647058823529 #> Calculating bloodmeal-human similarities #> Identifying matches #> # A tibble: 4 × 4 #>   bloodmeal_id human_id match similarity #>                      #> 1 evid1        P1       yes       0.294  #> 2 evid3        NA       no        0.0588 #> 3 evid2        NA       no       NA      #> 4 evid4        NA       no       NA"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_static_thresh.html","id":null,"dir":"Reference","previous_headings":"","what":"Match bloodmeals and humans based on log10LR static threshold — match_static_thresh","title":"Match bloodmeals and humans based on log10LR static threshold — match_static_thresh","text":"Match bloodmeals humans based log10LR static threshold","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_static_thresh.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Match bloodmeals and humans based on log10LR static threshold — match_static_thresh","text":"","code":"match_static_thresh(log10_lrs, thresh)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_static_thresh.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Match bloodmeals and humans based on log10LR static threshold — match_static_thresh","text":"log10_lrs Output calc_log10_lrs() bistro return_lrs = TRUE (lrs: second element list) thresh log10LR threshold matching. bloodmeal-human pairs log10LR ≥ thresh considered match.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_static_thresh.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Match bloodmeals and humans based on log10LR static threshold — match_static_thresh","text":"Dataframe including columns similar bistro() output.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/match_static_thresh.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Match bloodmeals and humans based on log10LR static threshold — match_static_thresh","text":"","code":"bistro_output <- bistro(bloodmeal_profiles, human_profiles,   pop_allele_freqs = pop_allele_freqs,   kit = \"ESX17\", peak_thresh = 200, return_lrs = TRUE ) #> 1/17 markers in kit but not in pop_allele_freqs: AMEL #> Formatting bloodmeal profiles #> Removing 6 peaks under the threshold of 200 RFU. #> For 1/4 bloodmeal ids, all peaks are below the threshold #> Formatting human profiles #> Markers being used: D10S1248, D12S391, D16S539, D18S51, D19S433, D1S1656, D21S11, D22S1045, D2S1338, D2S441, D3S1358, D8S1179, FGA, SE33, TH01, VWA #> Calculating log10LRs #> # bloodmeal ids: 3 #> # human ids: 3 #> Bloodmeal id 1/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Bloodmeal id 2/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Bloodmeal id 3/3 #> Human id 1/3 #> Human id 2/3 #> Human id 3/3 #> Identifying matches match_static_thresh(bistro_output$lrs, 10) #> # A tibble: 4 × 6 #>   bloodmeal_id locus_count est_noc match human_id log10_lr #>                              #> 1 evid1                 16       2 yes   P1           21.8 #> 2 evid1                 16       2 yes   P2           10.3 #> 3 evid2                  1       2 no    NA           NA   #> 4 evid3                  8       1 no    NA           NA"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/pop_allele_freqs.html","id":null,"dir":"Reference","previous_headings":"","what":"Human population allele frequencies — pop_allele_freqs","title":"Human population allele frequencies — pop_allele_freqs","text":"Example population allele frequencies EuroForMix (ESX17_Norway)","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/pop_allele_freqs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Human population allele frequencies — pop_allele_freqs","text":"","code":"pop_allele_freqs"},{"path":[]},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/pop_allele_freqs.html","id":"pop-allele-freqs-a-data-frame-with-rows-and-columns-the","dir":"Reference","previous_headings":"","what":"pop_allele_freqs A data frame with 76 rows and 17 columns. The","title":"Human population allele frequencies — pop_allele_freqs","text":"first column STR allele following columns frequency allele different markers.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/pop_allele_freqs.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Human population allele frequencies — pop_allele_freqs","text":"http://euroformix.com/","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_bloodmeal_profiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Preprocess bloodmeal profiles — prep_bloodmeal_profiles","title":"Preprocess bloodmeal profiles — prep_bloodmeal_profiles","text":"Removes duplicates peaks threshold, subsets ids","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_bloodmeal_profiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Preprocess bloodmeal profiles — prep_bloodmeal_profiles","text":"","code":"prep_bloodmeal_profiles(   bloodmeal_profiles,   bloodmeal_ids = NULL,   peak_thresh = NULL,   rm_markers = c(\"AMEL\"),   check_heights = TRUE )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_bloodmeal_profiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Preprocess bloodmeal profiles — prep_bloodmeal_profiles","text":"bloodmeal_profiles Tibble alleles bloodmeals reference database including 4 columns: SampleName, Marker, Allele, Height. Height must numeric coercible numeric. bloodmeal_ids Vector bloodmeal ids SampleName column bloodmeal_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL peak_thresh Allele peak height threshold RFUs. peaks threshold filtered . prior filtering performed, number equal greater number. Also used threshT argument euroformix::contLikSearch(). rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations. check_heights boolean indicating whether check peak heights threshold. Default: TRUE","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_bloodmeal_profiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Preprocess bloodmeal profiles — prep_bloodmeal_profiles","text":"Dataframe preprocessed bloodmeal profiles","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_human_profiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Preprocess human profiles — prep_human_profiles","title":"Preprocess human profiles — prep_human_profiles","text":"Removes duplicates optionally twins, subsets ids","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_human_profiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Preprocess human profiles — prep_human_profiles","text":"","code":"prep_human_profiles(   human_profiles,   human_ids = NULL,   rm_twins = TRUE,   rm_markers = c(\"AMEL\") )"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_human_profiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Preprocess human profiles — prep_human_profiles","text":"human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele. human_ids Vector human ids SampleName column human_profiles compute log10_lrs. NULL, ids input dataframe used. Default: NULL rm_twins boolean indicating whether remove likely twins (identical STR profiles) human database prior identifying matches. Default: TRUE rm_markers vector indicating markers removed prior calculating log10LRs. NULL include markers. default, bistro function AMEL removed standard include LR calculations.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/prep_human_profiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Preprocess human profiles — prep_human_profiles","text":"Dataframe preprocessed human profiles","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_dups.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove duplicate rows with warning — rm_dups","title":"Remove duplicate rows with warning — rm_dups","text":"Remove duplicate rows warning","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_dups.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove duplicate rows with warning — rm_dups","text":"","code":"rm_dups(df)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_dups.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove duplicate rows with warning — rm_dups","text":"df Dataframe remove duplicate rows","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_dups.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove duplicate rows with warning — rm_dups","text":"Un-duplicated dataframe","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_markers.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove markers — rm_markers","title":"Remove markers — rm_markers","text":"Remove markers","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_markers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove markers — rm_markers","text":"","code":"rm_markers(profiles, markers)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_markers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove markers — rm_markers","text":"df Dataframe remove markers","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_markers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove markers — rm_markers","text":"Dataframe without markers","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_twins.html","id":null,"dir":"Reference","previous_headings":"","what":"Remove identical STR profiles — rm_twins","title":"Remove identical STR profiles — rm_twins","text":"Remove identical STR profiles","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_twins.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Remove identical STR profiles — rm_twins","text":"","code":"rm_twins(human_profiles)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_twins.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Remove identical STR profiles — rm_twins","text":"human_profiles Tibble alleles humans reference database including three columns: SampleName, Marker, Allele.","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/rm_twins.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Remove identical STR profiles — rm_twins","text":"Data frame twins removed","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/subset_ids.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset to ids present in the dataset — subset_ids","title":"Subset to ids present in the dataset — subset_ids","text":"Subset ids present dataset","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/subset_ids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset to ids present in the dataset — subset_ids","text":"","code":"subset_ids(ids, vec, vec_name)"},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/subset_ids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subset to ids present in the dataset — subset_ids","text":"ids ids check vec vec vector ids vec_name name vector","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/reference/subset_ids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subset to ids present in the dataset — subset_ids","text":"list IDs present","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/news/index.html","id":"bistro-011","dir":"Changelog","previous_headings":"","what":"bistro 0.1.1","title":"bistro 0.1.1","text":"Add DOI","code":""},{"path":"https://duke-malaria-collaboratory.github.io/bistro/news/index.html","id":"bistro-010","dir":"Changelog","previous_headings":"","what":"bistro 0.1.0","title":"bistro 0.1.0","text":"Initial package development. bistro() match_exact() match_similarity() match_static_thresh() Includes introductory vignette.","code":""}]