The idea is to create a framework addressing some of the following scenarios
NOTE: These have been tested limitedly, please file a bug report in-case of errors.
# install flowr
Rscript -e 'install.packages("flowr")'
Rscript -e 'library(flowr);flowr::setup()'
git clone https://github.com/flow-r/ultraseq.git
flowr devtools::install pkg=ultraseq/ultraseq
scenario 1
# create a table of fastq files to use
flowr create_sample_sheet
# create a set of commands to run
flowr run ultraseq
# execute commands on the cluster
flowr to_flow
scenario 2
start by using a single bam
flowr run -h
flowr run ultraseq
flowr run ultraseq tbam=$tbam nbam=$nbam oprefix=$oprefix
This repository has the folling structure.
Folder pipelines, contains several pipelines used in cancer genome analysis.
The ultraseq folder contains a R package, with unit tests and vinettes and a stable source code
enabling the pipelines. Using a R package streamlines, tesinting, building and documentation.
├── pipelines
│ ├── bam_preprocess.R
│ ├── fastq_bam_bwa.R
│ ├── fastq_haplotyper.R
│ ├── fastq_mutect.R
│ ├── fastq_mutect_mem.R
│ ├── fastq_mutect_old.R
│ ├── fastq_preprocess.R
│ └── ultraseq.R
└── ultraseq
├── R
│ ├── annotate.R
│ ├── bwa.R
│ ├── chipseq.R
│ ├── depthofcoverage.R
│ ├── fastqc.R
│ ├── fetch_genomes.R
│ ├── freebayes.R
│ ├── generic.R
│ ├── haplotyper.R
│ ├── modules.R
│ ├── mut2maf.R
│ ├── mutect.R
│ ├── parse_vcf.R
│ ├── picard.R
│ ├── preprocess.R
│ ├── samblaster.R
│ ├── samtools.R
│ ├── scripture.R
│ ├── sheets_fastqs.R
│ ├── split_fq.R
│ ├── star.R
│ └── zzz.R
├── inst
│ ├── conf
│ └── scripts
├── man
└── vignettes
# install dependencies
Rscript -e 'install.packages("flowr", repos = "http://cran.rstudio.com")'
# install ultraseq package, from this repository
devtools::install_github("flow-r/ultraseq", subdir = "ultraseq")
# get somatic variant calling workflows
git clone https://github.com/sahilseth/ultraseq.git