From 215aa2af21dae925e38f1ab495b3e279847361f3 Mon Sep 17 00:00:00 2001 From: jonca79 Date: Tue, 15 Oct 2024 13:00:43 +0200 Subject: [PATCH] docs: update documentaion --- docs/dna_biomarkers.md | 16 +++--- docs/dna_cnvs.md | 103 +++++++++++++++++++++++------------ docs/dna_fusions.md | 8 +-- docs/dna_qc.md | 4 +- docs/dna_snv_indels.md | 8 +-- docs/images/cnvs.dot | 6 +++ docs/images/cnvs.png | Bin 102362 -> 123268 bytes docs/references.md | 109 +++++++------------------------------- docs/rna_exon_skipping.md | 2 +- docs/rna_fusions.md | 20 +++---- docs/rna_id_snps.md | 2 +- docs/rna_qc.md | 2 +- 12 files changed, 126 insertions(+), 154 deletions(-) diff --git a/docs/dna_biomarkers.md b/docs/dna_biomarkers.md index 55def58a..da7a3b24 100644 --- a/docs/dna_biomarkers.md +++ b/docs/dna_biomarkers.md @@ -6,10 +6,10 @@ See the [biomarkers hydra-genetics module](https://hydra-genetics-biomarker.read ## Pipeline output files: -* `results/dna/tmb/{sample}_{type}.TMB.txt` -* `results/dna/msi/{sample}_{type}.msisensor_pro.score.tsv` -* `results/dna/hrd/{sample}_{type}.purecn.scarhrd_cnvkit_score.txt` -* `results/dna/hrd/{sample}_{type}.pathology.scarhrd_cnvkit_score.txt` +* `results/dna/{sample}_{type}/tmb/{sample}_{type}.TMB.txt` +* `results/dna/{sample}_{type}/msi/{sample}_{type}.msisensor_pro.score.tsv` +* `results/dna/{sample}_{type}/hrd/{sample}_{type}.purecn.scarhrd_cnvkit_score.txt` +* `results/dna/{sample}_{type}/hrd/{sample}_{type}.pathology.scarhrd_cnvkit_score.txt` ## Tumor mutational burden (TMB) TMB is a measure of the frequency of somatic mutations and is usually measured as mutations per megabase. The size of design of the exons is approximately 1.55Mb. However, by validating the TMB for GMS560 against Foundation One and TSO500 TMB the effective design size is adjusted to 1.19Mb. This is based on the slope (0.84) of the correlation between TSO500 data and the number of variants in the TMB analysis. The TMB is calculated using the in-house script **[tmb.py](https://github.com/hydra-genetics/biomarker/blob/develop/workflow/scripts/tmb.py)** ([rule](https://github.com/hydra-genetics/biomarker/blob/develop/workflow/rules/tmb.smk)) which counts the number of nsSNVs and divide by the adjusted design size. Variants must fulfill the following criteria to be counted: @@ -36,7 +36,7 @@ The result is the TMB calculated using nsSNVs. However, the variants passing all ### Result file -* `results/dna/tmb/{sample}_{type}.TMB.txt` +* `results/dna/{sample}_{type}/tmb/{sample}_{type}.TMB.txt` ## Microsatellite instability (MSI) To determine MSS or MSI status of the samples the percentage of sites that have microsatellite instability are calculated using **[MSIsensor-pro]([https://github.com/xjtu-omics/msisensor-pro])** v1.1.a. When more than 10% of the sites are instable the sample is determined to have MSI status. The program uses a panel of normal to determine the normal level of instability in the used sites. @@ -48,7 +48,7 @@ To determine MSS or MSI status of the samples the percentage of sites that have ### Result file -* `results/dna/msi/{sample}_{type}.msisensor_pro.score.tsv` +* `results/dna/{sample}_{type}/msi/{sample}_{type}.msisensor_pro.score.tsv` ## Homologous recombination deficiency (HRD) - in development **OBS! The Homologous recombination deficiency score is still under development** @@ -69,7 +69,7 @@ A homologous recombination deficiency score is calculated using **[scarHRD](http ### Result files -* `results/dna/hrd/{sample}_{type}.purecn.scarhrd_cnvkit_score.txt` -* `results/dna/hrd/{sample}_{type}.pathology.scarhrd_cnvkit_score.txt` +* `results/dna/{sample}_{type}/hrd/{sample}_{type}.purecn.scarhrd_cnvkit_score.txt` +* `results/dna/{sample}_{type}/hrd/{sample}_{type}.pathology.scarhrd_cnvkit_score.txt`
diff --git a/docs/dna_cnvs.md b/docs/dna_cnvs.md index b005ad52..99412aab 100644 --- a/docs/dna_cnvs.md +++ b/docs/dna_cnvs.md @@ -3,6 +3,7 @@ See the [cnv hydra-genetics module](https://hydra-genetics-snv-indels.readthedoc
![purecn dag plot](images/cnv_purecn.png){: style="height:55%;width:55%"} +
![manta dag plot](images/cnv_manta.png){: style="height:30%;width:30%"}
@@ -11,16 +12,32 @@ See the [cnv hydra-genetics module](https://hydra-genetics-snv-indels.readthedoc ## Pipeline output files: -* `results/dna/cnv/{sample}_{type}/{sample}_{type}.pathology.cnv.html` -* `results/dna/cnv/{sample}_{type}/{sample}_{type}.pathology.cnv_report.tsv` -* `results/dna/cnv/{sample}_{type}/{sample}_{type}.purecn.cnv.html` -* `results/dna/cnv/{sample}_{type}/{sample}_{type}.purecn.cnv_report.tsv` -* `results/dna/additional_files/cnv/{sample}_{type}/{sample}_{type}.deletions.tsv` -* `results/dna/additional_files/cnv/{sample}_{type}/{sample}_{type}.amplifications.tsv` -* `results/dna/additional_files/cnv/{sample}_{type}/{sample}_{type}.manta_tumorSV.vcf.gz` +### Main output + +* `results/dna/{sample}_{type}/cnv/{sample}_{type}.pathology_purecn.cnv.html` +* `results/dna/{sample}_{type}/cnv/{sample}_{type}.pathology_purecn.amp_all_del_validated.cnv_report.tsv` +* `results/dna/{sample}_{type}/cnv/{sample}_{type}.purecn_purity_ploidity.csv` + +### Additional output +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.amplifications.tsv` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.deletions.tsv` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.cnvkit.diagram.pdf` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.cnvkit.scatter.png` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.manta_tumorSV.vcf.gz` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.pathology.amp_all_del_all.cnv_report.tsv` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.pathology.amp_all_del_validated.cnv_report.tsv` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.pathology.cnv.html` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.pathology_purecn.amp_all_del_all.cnv_report.tsv` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.pathology_purecn.svdb_query.vcf` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.pathology.svdb_query.vcf` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.purecn.amp_all_del_all.cnv_report.tsv` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.purecn.amp_all_del_validated.cnv_report.tsv` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.purecn.cnv.html` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.purecn.svdb_query.vcf` + ## CNV calling -CNVs are called using both CNVkit and GATK CNV, followed by merging and annotation by SVDB and finally filtered and visualized into an html report. Additionally, smaller CNV deletions and amplifications are called in specific genes using an in-house script. +CNVs are called using CNVkit, GATK CNV, and Jumble followed by merging and annotation by SVDB and finally filtered and visualized into an html report. Additionally, smaller CNV deletions and amplifications are called in specific genes using an in-house script. ### CNVkit CNV segmentation is performed by **[CNVkit](https://cnvkit.readthedocs.io/en/stable/)** v0.9.9 on BWA-mem aligned and merged bam-files. CNVkit uses a panel of normal (see [references](references.md) on how the PoN was created) and a germline filtered vcf file. To call the final CNVs the program uses the estimated tumor purity, which can be from pathologists estimates or from purecn estimates. @@ -49,8 +66,18 @@ The following steps are in included in the GATK CNV calling: | ModelSegments | Make raw segmentation | | | | CallCopyRatioSegments | Refine segmentation and call CNVs | | | +### Jumble +CNV segmentation is performed by **[Jumble](https://github.com/ClinSeq/jumble)** on BWA-mem aligned and merged bam-files. Jumble uses a panel of normal (see [references](references.md) on how the PoN was created) and a germline filtered vcf file. To call the final CNVs the CNVkit call script is used with the estimated tumor purity as input, which can be from pathologists estimates or from purecn estimates. +The following steps are in included in the Jumble CNV calling: + +| Rule | Info | Settings | Description | +|-|-|-|-| +| run | Makes segmentation | [RDS reference](references.md#jumble_ref) | Panel of normal which can include data from different sequencing machines | +| call | Calls CNVs | [Germline vcf](dna_cnvs.md#germline-vcf) | Vcf with germline variants called in the sample | +| | | Tumor purity | Estimated purity from samples.tsv or from other sources | + ## CNV call file conversion to vcf -The CNVs call files from CNVkit and GATK CNV are converted to vcf format using the in-house scripts [cnvkit_vcf.py](https://github.com/hydra-genetics/cnv_sv/blob/develop/workflow/scripts/cnvkit_vcf.py) ([rule](https://github.com/hydra-genetics/cnv_sv/blob/develop/workflow/rules/cnvkit.smk)) and [gatk_to_vcf.py](https://github.com/hydra-genetics/cnv_sv/blob/develop/workflow/scripts/gatk_to_vcf.py) ([rule](https://github.com/hydra-genetics/cnv_sv/blob/develop/workflow/rules/gatk.smk)). In both cases a vcf header is added followed by the following annotation for each field in the vcf file: +The CNVs call files from CNVkit and Jumble are converted to vcf format using the in-house scripts [cnvkit_vcf.py](https://github.com/hydra-genetics/cnv_sv/blob/develop/workflow/scripts/cnvkit_vcf.py) ([cnvkit_vcf](https://github.com/hydra-genetics/cnv_sv/blob/develop/workflow/rules/cnvkit.smk), [jumble_vcf](https://github.com/hydra-genetics/cnv_sv/blob/develop/workflow/rules/jumble.smk)) and GATK CNV by [gatk_to_vcf.py](https://github.com/hydra-genetics/cnv_sv/blob/develop/workflow/scripts/gatk_to_vcf.py) ([gatk_to_vcf](https://github.com/hydra-genetics/cnv_sv/blob/develop/workflow/rules/gatk.smk)). In all cases a vcf header is added followed by the following annotation for each field in the vcf file: | **Column** | **Value / Description** | |---------------|--------------------| @@ -73,9 +100,9 @@ The CNVs call files from CNVkit and GATK CNV are converted to vcf format using t | END | CNV end position | | SVLEN | CNV length | | LOG_ODDS_RATIO | CNV log odds copy ratio (0 = 2 copies) | -| CALLER | cnvkit / gatk | +| CALLER | cnvkit / gatk / jumble | | CN | Copy number (NA for CNVkit) | -| CORR_CN | Purity corrected copy number (calculated for GATK CNV and reported for CNVkit) | +| CORR_CN | Purity corrected copy number (calculated for GATK CNV and reported for CNVkit and Jumble) | | PROBES | Number of probes within the cnv segment | | BAF | SNP minor allele frequency | @@ -85,10 +112,10 @@ The CNVs call files from CNVkit and GATK CNV are converted to vcf format using t | **FORMAT / DATA tag** | **Value / Description** | |------------|-------------------------------------------------------------------------------------------------------------------| | GT | Genotype: 1/1 for homozygous deletion, 1/0 for heterozygous deletion and or duplication, and 0/0 for copy neutral | -| CN | Copy number (corrected for CNVkit and uncorrected for GATK CNV) | +| CN | Copy number (corrected for CNVkit and Jumble and uncorrected for GATK CNV) | | CCN | Corrected copy number (GATK CNV only) | | CNQ | Number of probes in CNV | -| DP | Average coverage over region (cnvkit only) | +| DP | Average coverage over region (CNVkit and Jumble only) | | BAF | SNP minor allele frequency | | BAFQ | Number of SNPs for BAF (GATK CNV only) | @@ -113,6 +140,7 @@ SVDB --merge | **Options** | **Value** | **Description** | |-------------|-|-| +| overlap | 1 | Merge the two vcf files without actually merging overlapping regions | | extra | --pass_only | Merge the two vcf files without actually merging overlapping regions |
@@ -174,7 +202,7 @@ CNVkit and GATK CNV sometimes miss small deletions where only a number of exons ### Result file -* `results/dna/additional_files/cnv/{sample}_{type}/{sample}_{type}.deletions.tsv` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.deletions.tsv` ## Small CNV amplifications CNVkit and GATK CNV sometimes miss small amplifications where only a number of exons are involved. A specialized small CNV caller in the form of the in-house script [call_small_cnv_amplifications.py](https://github.com/genomic-medicine-sweden/Twist_Solid/blob/develop/workflow/scripts/call_small_cnv_amplifications.py) ([rule and config](softwares.md#call_small_cnv_amplifications)) is therefore run on the genes mentioned in [CNV gene annotation](#cnv-gene-annotation). The caller uses the log-odds values calculated by GATK for each region, where a region approximately corresponds to one region in the design file, i.e. exon, intron (if present) or CNV-probe. For each gene region, the caller uses a sliding window to find the biggest increase and subsequent decrease in copy number in the region. It then determines if the increase in copy number is big enough and is significantly higher than the surrounding region. If a large part or the entire region is amplified it will not be called but will instead be called by the other tools. @@ -192,7 +220,7 @@ CNVkit and GATK CNV sometimes miss small amplifications where only a number of e ### Result file -* `results/dna/additional_files/cnv/{sample}_{type}/{sample}_{type}.amplifications.tsv` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.amplifications.tsv` ## CNV report (.tsv) A combined cnv report in tsv format is generated by the in-house script [cnv_report.py](https://github.com/genomic-medicine-sweden/Twist_Solid/blob/develop/workflow/scripts/cnv_report.py) ([rule and config](softwares.md#cnv_tsv_report)). The report extract cnv variants from the vcf files with filtered cnv calls as well as the small amplification and deletion files. The script also looks for 1p19q deletions and add that to the report. @@ -208,46 +236,55 @@ A combined cnv report in tsv format is generated by the in-house script [cnv_rep ### Result files -* `results/dna/cnv/{sample}_{type}/{sample}_{type}.pathology_purecn.cnv_report.tsv` +* `results/dna/{sample}_{type}/cnv/{sample}_{type}.pathology_purecn.cnv_report.tsv` ## CNV visualization (.html) -In addition to the tsv report, an html report is also generated which provides a visualization of the underlying data as well as CNV information. +In addition to the tsv report, an html report is also generated which provides a visualization of the underlying data as well as CNV information. An extra table for small deletions, small amplifications and 1p19q deletions as well as a table for large copy number aberrations are also provided. ### Configuration **Software settings** ```yaml -# config.yaml +# config/config.yaml cnv_html_report: - show_table: true - template_dir: config/cnv_report_template + show_table: true + cytobands: true + extra_tables: + - name: Small CNVs and 1p19q + description: > + Additional small amplifications and deletions as well as 1p19q co-deletions called by Twist Solid + in-house scripts. Can have overlaps with called regions from other callers. + path: "cnv_sv/svdb_query/{sample}_{type}.{tc_method}.cnv_loh_genes_all.cnv_additional_variants_only.tsv" + - name: Large chromosomal aberrations + description: > + Large chromosomal aberrations in the form of deletions, duplications and copy neutral loss of heterozygosity. + Also warnings of baseline skewness and detection of polyploidy in the sample. + path: "cnv_sv/svdb_query/{sample}_{type}.{tc_method}.cnv_loh_genes_all.cnv_chromosome_arms.tsv" merge_cnv_json: - annotations: - - /projects/wp1/nobackup/ngs/utveckling/Twist_DNA_DATA/bed/cnv_amp_genes.bed - - /projects/wp1/nobackup/ngs/utveckling/Twist_DNA_DATA/bed/cnv_loh_genes.bed filtered_cnv_vcfs: - - cnv_sv/svdb_query/{sample}_{type}.{tc_method}.svdb_query.annotate_cnv.cnv_amp_genes.filter.cnv_hard_filter_amp.vcf.gz - - cnv_sv/svdb_query/{sample}_{type}.{tc_method}.svdb_query.annotate_cnv.cnv_loh_genes_all.filter.cnv_hard_filter_loh.vcf.gz - unfiltered_cnv_vcfs: - - cnv_sv/svdb_query/{sample}_{type}.{tc_method}.svdb_query.annotate_cnv.cnv_amp_genes.vcf.gz - - cnv_sv/svdb_query/{sample}_{type}.{tc_method}.svdb_query.annotate_cnv.cnv_loh_genes_all.vcf.gz + - cnv_sv/svdb_query/{sample}_{type}.{tc_method}.svdb_query.annotate_cnv.cnv_amp_genes.filter.cnv_hard_filter_amp.fp_tag.vcf + - cnv_sv/svdb_query/{sample}_{type}.{tc_method}.svdb_query.annotate_cnv.cnv_loh_genes_all.filter.cnv_hard_filter_loh.fp_tag.annotate_fp.vcf germline_vcf: snv_indels/bcbio_variation_recall_ensemble/{sample}_{type}.ensembled.vep_annotated.filter.germline.exclude.blacklist.vcf.gz + unfiltered_cnv_vcfs: + - cnv_sv/svdb_query/{sample}_{type}.{tc_method}.svdb_query.annotate_cnv.cnv_amp_genes.fp_tag.vcf.gz + - cnv_sv/svdb_query/{sample}_{type}.{tc_method}.svdb_query.annotate_cnv.cnv_loh_genes_all.fp_tag.vcf.gz + unfiltered_cnv_vcfs_tbi: + - cnv_sv/svdb_query/{sample}_{type}.{tc_method}.svdb_query.annotate_cnv.cnv_amp_genes.fp_tag.vcf.gz.tbi + - cnv_sv/svdb_query/{sample}_{type}.{tc_method}.svdb_query.annotate_cnv.cnv_loh_genes_all.fp_tag.vcf.gz.tbi ``` -The attribute `cnv_html_report.show_table` determines whether a table of CNV calls should be generated. It this is true, then the attributes `merge_cnv_json.filtered_cnv_vcfs` and `merge_cnv_json.unfiltered_cnv_vcfs` are required. The optional attribute `merge_cnv_json.annotations` is an array of bed-files with annotations that will be added to the chromosome plot of the report. Finally, `merge_cnv_json.germline_vcf` should be a VCF file with germline variants annotated with allele frequency that will be used to populate the VAF-plots in the report. - For more information, see the [hydra-genetics/reports documentation](https://hydra-genetics-reports.readthedocs.io). ### Result files -* `results/dna/cnv/{sample}_{type}/{sample}_{type}.pathology_purecn.cnv.html` +* `results/dna/{sample}_{type}/cnv/{sample}_{type}.pathology_purecn.cnv.html` ## Germline vcf -The germline vcf used by CNVkit and the CNV html report is based on the [VEP annotated vcf](dna_snv_indels.md#vep) file from the SNV and INDEL calling. Annotated vcfs are hard filtered first by removing black listed regions with noisy germline VAFs in normal samples and then filtered by a number of filtering criteria described below. See the [filtering hydra-genetics module](https://filtering.readthedocs.io/en/latest/) for additional information. +The germline vcf used by CNVkit, Jumble, and the CNV html report is based on the [VEP annotated vcf](dna_snv_indels.md#vep) file from the SNV and INDEL calling. Annotated vcfs are hard filtered first by removing black listed regions with noisy germline VAFs in normal samples and then filtered by a number of filtering criteria described below. See the [filtering hydra-genetics module](https://filtering.readthedocs.io/en/latest/) for additional information. ### Exclude exonic regions Use **[bcftools filter -T](https://samtools.github.io/bcftools/bcftools.html)** v1.15 to exclude variants overlapping blacklisted regions defined in a bed file. @@ -323,6 +360,6 @@ PureCN uses a filtered (`config/config_hard_filter_purecn.yaml`) and germline an ### Result file -* `results/dna/additional_files/cnv/{sample}_{type}/{sample}_{type}.manta_tumorSV.vcf.gz` +* `results/dna/{sample}_{type}/additional_files/cnv/{sample}_{type}.manta_tumorSV.vcf.gz`
diff --git a/docs/dna_fusions.md b/docs/dna_fusions.md index 2dac4bec..a66933c5 100644 --- a/docs/dna_fusions.md +++ b/docs/dna_fusions.md @@ -6,8 +6,8 @@ See the [fusions hydra-genetics module](https://hydra-genetics-fusions.readthedo ## Pipeline output files: -* `results/dna/fusion/{sample}_{type}.gene_fuse_report.tsv` (with UMI option only) -* `results/dna/fusion/{sample}_{type}.fuseq_wes.report.csv` +* `results/dna/{sample}_{type}/fusion/{sample}_{type}.gene_fuse_report.tsv` (with UMI option only) +* `results/dna/{sample}_{type}/fusion/{sample}_{type}.fuseq_wes.report.csv` ## Fusions calling using GeneFuse DNA fusion calling is performed by **[GeneFuse](https://github.com/OpenGene/GeneFuse)** v0.6.1 on fastq-files. It uses a gene transcript target file to limit the number of targets to analyze. @@ -49,7 +49,7 @@ The output from GeneFuse is filtered and then reported into a fusion report usin ### Result file -* `results/dna/fusion/{sample}_{type}.gene_fuse_report.tsv` +* `results/dna/{sample}_{type}/fusion/{sample}_{type}.gene_fuse_report.tsv`
@@ -98,6 +98,6 @@ The output from FuSeq_WES is filtered and then reported into a fusion report usi ### Result file -* `results/dna/fusion/{sample}_{type}.fuseq_wes_report.tsv` +* `results/dna/{sample}_{type}/fusion/{sample}_{type}.fuseq_wes_report.tsv`
diff --git a/docs/dna_qc.md b/docs/dna_qc.md index 059f35fc..16b4ed1a 100644 --- a/docs/dna_qc.md +++ b/docs/dna_qc.md @@ -7,7 +7,7 @@ See the [qc hydra-genetics module](https://hydra-genetics-qc.readthedocs.io/en/l ## Pipeline output files: * `results/dna/qc/multiqc_DNA.html` -* `results/dna/qc/{sample}_{type}.coverage_and_mutations.tsv` +* `results/dna/{sample}_{type}/qc/{sample}_{type}.coverage_and_mutations.tsv` * `gvcf_dna/{sample}_{type}.mosdepth.g.vcf.gz` ## MultiQC @@ -107,6 +107,6 @@ levels: ### Result file -* `results/dna/qc/{sample}_{type}.coverage_and_mutations.tsv` +* `results/dna/{sample}_{type}/qc/{sample}_{type}.coverage_and_mutations.tsv`
diff --git a/docs/dna_snv_indels.md b/docs/dna_snv_indels.md index 2e576d69..a054b336 100644 --- a/docs/dna_snv_indels.md +++ b/docs/dna_snv_indels.md @@ -6,8 +6,8 @@ See the [snv_indels hydra-genetics module](https://hydra-genetics-snv-indels.rea ## Pipeline output files: -* `results/dna/vcf/{sample}_{type}.annotated.exon_only.filter.hard_filter.codon_snv.vcf` -* `results/dna/vcf/{sample}_{type}.annotated.exon_only.filter.hard_filter.codon_snv.qci.vcf` +* `results/dna/{sample}_{type}/vcf/{sample}_{type}.annotated.exon_only.filter.hard_filter.codon_snv.vcf` +* `results/dna/{sample}_{type}/vcf/{sample}_{type}.annotated.exon_only.filter.hard_filter.codon_snv.qci.vcf` * `bam_dna/mutect2_indel_bam/{sample}_{type}.bam` @@ -203,14 +203,14 @@ Two or more variants affecting the same codon can have different clinical implic ### Result file -* `results/dna/vcf/{sample}_{type}.annotated.exon_only.filter.hard_filter.codon_snv.vcf` +* `results/dna/{sample}_{type}/vcf/{sample}_{type}.annotated.exon_only.filter.hard_filter.codon_snv.vcf` ## QCI AF correction of vcf The clinical interpretation tool QCI calculates allele frequency from the AD FORMAT field instead of using the AF FORMAT field supplied by the callers. This has shown to be wrong especially for INDELs. The AD field is therefore corrected so that the allele frequency based on the AD field corresponds to the AF field. This correction of the vcf file is performed by an the in-house script [fix_vcf_ad_for_qci.py](https://github.com/genomic-medicine-sweden/Twist_Solid/blob/develop/workflow/scripts/fix_vcf_ad_for_qci.py) ([rule and config](softwares.md#fix_vcf_ad_for_qci)). ### Result file -* `results/dna/vcf/{sample}_{type}.annotated.exon_only.filter.hard_filter.codon_snv.qci.vcf` +* `results/dna/{sample}_{type}/vcf/{sample}_{type}.annotated.exon_only.filter.hard_filter.codon_snv.qci.vcf` ## GATK Mutect2 variant bam file When **[GATK Mutect2](https://gatk.broadinstitute.org/hc/en-us/articles/360037593851-Mutect2)** finds INDEL candidates it realignes reads in this regions and outputs a realigned bam-file covering these INDEL regions. This makes it possible to inspect INDELs called by Mutect2 in [IGV](https://software.broadinstitute.org/software/igv/). As Mutect2 runs on individual chromosomes these bam-files are then merged, sorted and indexed before. diff --git a/docs/images/cnvs.dot b/docs/images/cnvs.dot index 01cbc03d..19db4314 100644 --- a/docs/images/cnvs.dot +++ b/docs/images/cnvs.dot @@ -16,6 +16,8 @@ digraph snakemake_dag { 48[label = "cnvkit_vcf", color = "0.17 0.6 0.85", style="rounded"]; 49[label = "cnvkit_call", color = "0.23 0.6 0.85", style="rounded"]; 50[label = "cnvkit_batch", color = "0.59 0.6 0.85", style="rounded"]; + 52[label = "jumble_run", color = "0.59 0.6 0.85", style="rounded"]; + 53[label = "jumble_cnvkit_vcf", color = "0.17 0.6 0.85", style="rounded"]; 51[label = "bcftools_filter_exclude_region", color = "0.37 0.6 0.85", style="rounded"]; 56[label = "gatk_to_vcf", color = "0.18 0.6 0.85", style="rounded"]; 57[label = "gatk_model_segments", color = "0.63 0.6 0.85", style="rounded"]; @@ -25,6 +27,10 @@ digraph snakemake_dag { 90[label = "merge_json", color = "0.54 0.6 0.85", style="rounded"]; 91[label = 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ze#-8e^dVD9quvY=azize0NlmgG5ce;X}UGvg_J-v;kVnk$c}UgpnRgL?ks00Q5Ugs z;dp$n-uHg!NUEK#YD9RXF%7lkuo`b&Qbf@=Z+At96}zE@kdM|2`z1xm(UBjSyo*}) z6cs*rn)p!-y-~@R`wH^kU#>>WT}3|l`^e}2`!xUg*Bho80T%klZ{GDzb0hyD_FP&x JS5W)i{{pS?%XR<& diff --git a/docs/references.md b/docs/references.md index fce0d6fd..2379ca28 100644 --- a/docs/references.md +++ b/docs/references.md @@ -83,6 +83,7 @@ The following reference files, panel of normals and design files are needed to r |_ _|
transcript black list
| `fuseq_wes_transcript_black_list.txt` | |
hotspot_annotation
| hotspots | `Hotspots_combined_regions_nodups.csv` | |
hotspot_report
| hotspot_mutations | `Hotspots_combined_regions_nodups.csv` | +|
jumble_run
| normal_reference | `jumble.combined.filtered.50.PoN.hg19.RDS` | |
manta_config_t
| extra | `pool1_pool2.sort.merged.padded20.cnv200.hg19.split_fusion_genes.210608.bed.gz` | |
msisensor_pro
| PoN | `Msisensor_pro_reference_nextseq_36.list_baseline` | |
purecn
| extra | `mapping_bias_nextseq_27_hg19.rds` | @@ -161,22 +162,22 @@ wget https://data.broadinstitute.org/Trinity/CTAT_RESOURCE_LIB/GRCh37_gencode_v1 Files needed by Twist Solid that are generated by the reference pipeline are listed below. Many of the panel of normals are available to download from the Uppsala Owncloud solution but should preferably be generated on in-house data.
-**Note** -The input needed to create these files depend on the result files of the main pipeline itself, meaning that the samples need to be analysed with dummy panel of normals first. -
**Result files** -* `cnvkit.PoN.cnn` -* `gatk_cnv_panel_of_normal.hdf5` -* `Msisensor_pro_reference.list_baseline` -* `background_panel.tsv` -* `artifact_panel.tsv` -* `svdb_cnv.vcf` -* `normalDB_hg19.rds` -* `mapping_bias_nextseq_27_hg19.rds` +* `result/cnvkit.PoN.cnn` +* `result/gatk_cnv_panel_of_normal.hdf5` +* `result/design.preprocessed.interval_list` +* `result/jumble.PoN.RDS` +* `result/Msisensor_pro_reference.list_baseline` +* `result/background_panel.tsv` +* `result/artifact_panel.tsv` +* `result/svdb_cnv.vcf` +* `result/mapping_bias.rds` +* `result/purecn_normal_db.rds` +* `result/purecn_targets_intervals.txt` ### Create samples and units -Files and samples used in the generation of the panel of normals are specified in samples.tsv and units.tsv. Required files and header names are listed down below. +Files and samples used in the generation of the panel of normals are specified in samples.tsv and units.tsv. Required files are listed down below. Adapt out file specification (`workflow/rules/common_references.smk`) and comment out files that should not be generated. ### Run command @@ -186,16 +187,10 @@ snakemake --profile profiles/uppsala_ref/ -s workflow/Snakefile_references.smk ```
**Note** -The `units.tsv` file needs to be adapted depending which panel of normals are created (see below) and should contain all the samples needed to create the panel of normals. +The `units.tsv` file needs to be adapted depending which panel of normals are created and should contain all the samples needed to create the panel of normals. ### CNVkit -**units.tsv** - -| Header | Data | Description | -|-|-|-| -| bam | `bam_dna/{sample}_{type}.bam` | Merged bam files created as output of the Twist Solid pipeline from normal FFPE samples | - **Reference files** * design bedfile @@ -204,12 +199,6 @@ The `units.tsv` file needs to be adapted depending which panel of normals are cr ### GATK CNV -**units.tsv** - -| Header | Data | Description | -|-|-|-| -| bam | `bam_dna/{sample}_{type}.bam` | Merged bam files created as output of the Twist Solid pipeline from normal FFPE samples | - **Reference files** * design bedfile @@ -218,12 +207,6 @@ The `units.tsv` file needs to be adapted depending which panel of normals are cr ### MSISensor-pro -**units.tsv** - -| Header | Data | Description | -|-|-|-| -| bam | `bam_dna/{sample}_{type}.bam` | Merged bam files created as output of the Twist Solid pipeline from normal FFPE samples | - **Reference files** * design bedfile @@ -237,11 +220,7 @@ The `units.tsv` file needs to be adapted depending which panel of normals are cr ### SVDB -**units.tsv** - -| Header | Data | Description | -|-|-|-| -| cnv_vcf | `results/dna/additional_files/cnv/{sample}_{type}/{sample}_{type}.pathology_purecn.svdb_query.vcf` | SVDB merged CNV vcf files created as output of the
Twist Solid pipeline from both normal and
tumor FFPE samples | +Should be made up of both normal and tumor FFPE samples! **Software settings** @@ -251,19 +230,11 @@ The `units.tsv` file needs to be adapted depending which panel of normals are cr ### Artifacts -**units.tsv** - -| Header | Data | Description | -|-|-|-| -| vcf | `results/dna/additional_files/vcf/{sample}_{type}.annotated.vcf.gz` | Unfiltered and merged vcf files created as output of the Twist Solid pipeline
from normal FFPE samples | +Based on unfiltered and merged vcf files from normal FFPE samples ### Background -**units.tsv** - -| Header | Data | Description | -|-|-|-| -| gvcf | `gvcf_dna/{sample}_{type}.mosdepth.g.vcf.gz` | Genome vcf files from Mutect2 created as output of the Twist Solid pipeline
from normal FFPE samples | +Based on genome vcf files from Mutect2 from normal FFPE samples **Software settings** @@ -273,50 +244,8 @@ The `units.tsv` file needs to be adapted depending which panel of normals are cr | max_af | 0.015 | Max allele frequency to be included (default: 0.015) | ### PureCN -**OBS!** The vcf files used for purecn are not the same as in other steps meaning that currently the refence pipeline will have to be run twice. Also the vcfs used are not a final output file of the pipeline so use --notemp when running. - -#### Target interval file -Target interval file for hg19 with 25000 in target bin size also including of target regions. -```bash -singularity docker://hydragenetics/purecn:2.2.0 Rscript $PURECN/IntervalFile.R --fasta ${fasta_ref} --in-file ${design_bed} --out-file ${intervals_file} --export ${optimized_bed} --genome hg19 --average-off-target-width 25000 --off-target -``` - -#### PureCN Panel of normal -**units.tsv** - -| Header | Data | Description | -|-|-|-| -| bam | `bam_dna/{sample}_{type}.bam` | Merged bam files created as output of the Twist Solid pipeline from
normal FFPE samples | -| vcf | `cnv_sv/purecn_modify_vcf/`
`{sample}_{type}.normalized.sorted.vep_annotated.filter.snv_hard_filter_purecn`
`.bcftools_annotated_purecn.mbq.vcf.gz` | Hard filtered vcf files for purecn created as intermediate output of the Twist Solid pipeline
from normal FFPE samples | - -**Software settings** - -| Options | Value | Description | -|-|-|-| -| intervals | Target interval file | File created by the command described above | +Made up of bam and vcf files from normal samples ## Pipeline specific files -These are design files and other pipeline specific files only available to download from out [git](https://github.com/genomic-medicine-sweden/Twist_Solid_pipeline_files) or the Uppsala Owncloud solution. - -| File type | File | Description | -|-|-|-| -| Design files | `pool1_pool2.sort.merged.padded20.cnv200.hg19.split_fusion_genes`
`.reannotated.210608.bed` | Design bed | -| | `pool1_pool2.sort.merged.padded20.cnv200.hg19.split_fusion_genes`
`.MUC6_31_rm.exon_only.reannotated.210608.bed` | Design bed file containing only exons | -| | `pool1_pool2.sort.merged.padded20.cnv200.hg19.split_fusion_genes`
`.MUC6_31_rm.exon_only.reannotated.210608.interval_list` | Design interval file containing only exons | -| | `pool1_pool2_nochr_3c.sort.merged.padded20.cnv400.hg19.210311.met`
`.annotated.bed.preprocessed.interval_list` | Design interval file used in GATK CNV PoN creation | -| | `Twist_RNA_Design5.annotated.bed` | RNA design bed | -| | `Twist_RNA_Design5.annotated.interval_list` | RNA design interval file | -|_ _| `ID_SNPs.bed` | List of RNA ID SNPs | -| Hotspots | `Hotspots_combined_regions_nodups.csv` | Positions, transcript information, etc on clinically relevant regions | -| GeneFuse | `GMS560_fusion_w_pool2.hg19.221117.csv` | Genes and its exonic positions included in fusion calling | -| | `filter_fusions_20221114.csv` | Filtering criteria for false positive prone fusion partners | -| FuSeq_WES | `fuseq_params.txt` | Filtering parameters used by FuSeq_WES | -| FuSeq_WES_report | `fuseq_wes_gene_white_list.txt` | Gene list for filtering of fusion | -| | `false_positive_fusion_pairs.txt` | Gene list for filtering of fusion | -|_ _| `fuseq_wes_transcript_black_list.txt` | Transcripts that should not be used in annotation | -| CNVkit | `cnvkit_germline_blacklist_20221221.bed` | List of regions excluded from the germline vcf file | -| GATK CNV | `gnomad_SNP_0.001_target.annotated.interval_list` | Bed file with CNV backbone SNPs which are selected from
GnomAD with over 0.1% global population frequency | -| Small CNV deletions | `cnv_deletion_genes.tsv` | File defining gene and its surrounding regions used for
small CNV deletion. Same deletion genes as used in the
CNV deletion reports | -| Small CNV amplifications | `cnv_amplification_genes.tsv` | File defining gene and its surrounding regions used for
small CNV amplification. Same amplification genes as used in the
CNV reports | -| Report RNA fusions | `Twist_RNA_fusionpartners.bed` | Bed file used for annotation of fusion partner exons | +Premade panel of normals, design files and references can be download using the hydra-genetics tools. Design files can also be downloaded for our [github repo](https://github.com/genomic-medicine-sweden/Twist_Solid_pipeline_files). Check the [config yaml files](https://github.com/genomic-medicine-sweden/Twist_Solid/tree/develop/config) in the Twist_Solid repo for the latest files. \ No newline at end of file diff --git a/docs/rna_exon_skipping.md b/docs/rna_exon_skipping.md index b535f45d..abc5b8c6 100644 --- a/docs/rna_exon_skipping.md +++ b/docs/rna_exon_skipping.md @@ -8,6 +8,6 @@ Exon skipping cannot be called by the fusion callers as they only search for fus ## Result file -* `results/rna/fusion/{sample}_{type}.exon_skipping.tsv` +* `results/rna/{sample}_{type}/fusion/{sample}_{type}.exon_skipping.tsv`
diff --git a/docs/rna_fusions.md b/docs/rna_fusions.md index 247481a0..fa139b86 100644 --- a/docs/rna_fusions.md +++ b/docs/rna_fusions.md @@ -5,11 +5,11 @@ Fusion calling is performed using three different fusion callers; [Arriba](https ## Pipeline output files: -* `results/rna/fusion/{sample}_{type}.fusion_report.tsv` -* `results/rna/additional_files/fusion/{sample}_{type}.arriba.fusions.tsv` -* `results/rna/fusion/{sample}_{type}.arriba.fusions.pdf` -* `results/rna/additional_files/fusion/{sample}_{type}.fusioncatcher.fusion_predictions.txt` -* `results/rna/additional_files/fusion/{sample}_{type}.star-fusion.fusion_predictions.tsv` +* `results/rna/{sample}_{type}/fusion/{sample}_{type}.fusion_report.tsv` +* `results/rna/{sample}_{type}/additional_files/fusion/{sample}_{type}.arriba.fusions.tsv` +* `results/rna/{sample}_{type}/fusion/{sample}_{type}.arriba.fusions.pdf` +* `results/rna/{sample}_{type}/additional_files/fusion/{sample}_{type}.fusioncatcher.fusion_predictions.txt` +* `results/rna/{sample}_{type}/additional_files/fusion/{sample}_{type}.star-fusion.fusion_predictions.tsv` ## Arriba @@ -80,7 +80,7 @@ Star aligned bam-files are used for fusion calling with [Arriba](https://github. ### Result file -* `results/rna/additional_files/fusion/{sample}_{type}.arriba.fusions.tsv` +* `results/rna/{sample}_{type}/additional_files/fusion/{sample}_{type}.arriba.fusions.tsv` ### Fusion images Arriba produces a pdf file containing a figure for every fusion called with a schematic presentation of the exons involved, breakpoints, coverage and directions of the fusion partners in the fusion. @@ -96,7 +96,7 @@ Arriba produces a pdf file containing a figure for every fusion called with a sc ### Result file -* `results/rna/fusion/{sample}_{type}.arriba.fusions.pdf` +* `results/rna/{sample}_{type}/fusion/{sample}_{type}.arriba.fusions.pdf` ## Star-Fusion [Star-Fusion](https://github.com/STAR-Fusion/STAR-Fusion) v1.10.1 uses Star to align merged fastq files but do so internally. @@ -121,7 +121,7 @@ Arriba produces a pdf file containing a figure for every fusion called with a sc ### Result file -* `results/rna/additional_files/fusion/{sample}_{type}.star-fusion.fusion_predictions.tsv` +* `results/rna/{sample}_{type}/additional_files/fusion/{sample}_{type}.star-fusion.fusion_predictions.tsv` ## Fusioncatcher [Fusioncatcher](https://github.com/ndaniel/fusioncatcher) v1.33 together with reference file package version 102 is used to call fusion from merged fastq files. @@ -145,7 +145,7 @@ Arriba produces a pdf file containing a figure for every fusion called with a sc ### Result file -* `results/rna/additional_files/fusion/{sample}_{type}.fusioncatcher.fusion_predictions.txt` +* `results/rna/{sample}_{type}/additional_files/fusion/{sample}_{type}.fusioncatcher.fusion_predictions.txt` ## Fusion filtering and report Fusion candidates from the three fusions callers are collected and filtered with different filtering options for each caller by the in-house script [report_fusions.py](https://github.com/genomic-medicine-sweden/Twist_Solid/blob/develop/workflow/scripts/report_fusions.py) ([rule and config](softwares.md#report_fusions)). The remaining fusion calls are then reported in a excel friendly tsv file. Fusions are filtered based on the number of reads cover the breakpoint. However, read pairs spanning the breakpoint are also reported together with total supporting reads as well as other annotations. The settings for respective caller are presented below: @@ -180,6 +180,6 @@ In the validation samples the MAML2 gene was falsely called frequently together ### Result file -* `results/rna/fusion/{sample}_{type}.fusion_report.tsv` +* `results/rna/{sample}_{type}/fusion/{sample}_{type}.fusion_report.tsv`
diff --git a/docs/rna_id_snps.md b/docs/rna_id_snps.md index 567d0e23..cb7f0785 100644 --- a/docs/rna_id_snps.md +++ b/docs/rna_id_snps.md @@ -26,6 +26,6 @@ The RNA design includes a number of probes covering SNPs that can be used to che ## Result file -* `results/rna/id_snps/{sample}_{type}.id_snps.vcf` +* `results/rna/{sample}_{type}/id_snps/{sample}_{type}.id_snps.vcf`
diff --git a/docs/rna_qc.md b/docs/rna_qc.md index e4f03cf0..c2687b86 100644 --- a/docs/rna_qc.md +++ b/docs/rna_qc.md @@ -5,7 +5,7 @@ See the [qc hydra-genetics module](https://hydra-genetics-qc.readthedocs.io/en/l ## Pipeline output files: * `results/rna/qc/multiqc_RNA.html` -* `results/rna/qc/{sample}_{type}.house_keeping_gene_coverage.tsv` +* `results/rna/{sample}_{type}/qc/{sample}_{type}.house_keeping_gene_coverage.tsv` ## MultiQC A MultiQC html report is generated using **[MultiQC](https://github.com/ewels/MultiQC)** v1.11. The report starts with a general statistics table showing the most important QC-values followed by additional QC data and diagrams. The qc data is generated using FastQC, mosdepth, samtools, and picard.