#' strelka2
#'
#' @description
#' Snvs and indels calling of paired tumor-normal wgs using manta
#'
#' @param normal Normal bam file.
#' @param tumor Tumour bam file.
#' @param ref Reference genome.
#' @param outPath Path where the output of the analysis will be saved.
#' @param cores Number of cores to use.
#' @param outName Name for the output file for the paired tumor normal analysis
#' @param indelCandidates For the somatic workflow, the best-practice recommendation is to run the Manta SV and indel caller on the same set of samples first, then supply Manta's candidate indels as input to Strelka
#'
#' @examples
#' \dontrun{
#'
#' normal <- 'raw/sample1_BL.bam'
#' tumor <- 'raw/sample1_TI.bam'
#' ref <- '/imppc/labs/lplab/share/marc/refgen/hg38/hg38.fa'
#' outPath <- 'dir/vcf'
#' cores <- 4
#' outName <- 'sample1'
#' indelCandidates <- /results/variants/candidateSmallIndels.vcf.gz
#' strelka2(normal = normal,
#' tumor = tumor,
#' ref = ref,
#' outPath = outPath,
#' cores = cores,
#' outName = outName)
#'
#' }
#' @export
# TODO germline mutations parse
strelka <- '/soft/bio/strelka-2.9.3'
strelka2 <- function(normal,
tumor,
ref,
outPath,
cores,
outName,
indelCandidates){
# configuration
outStrelka <- file.path(outPath, outName)
# create output directory if not exist
dir.create(outStrelka, showWarnings = FALSE)
confStrelka <- file.path(strelka, 'bin/configStrelka.py')
system(paste(confStrelka,
"--normalBam", normal,
"--tumorBam", tumor,
"--referenceFasta", ref,
"--runDir", outStrelka,
'--indelCandidates', indelCandidates))
# execution of job in the defined cores
runStrelka <- file.path(outStrelka, 'runWorkflow.py')
system(paste(runStrelka,
"-m local",
"-j", cores))
}
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