R/battenberg.R
In shaghayeghsoudi/Battenberg_customized: Battenberg subclonal copy number caller
Defines functions
battenberg
Documented in
battenberg
#' Run the Battenberg pipeline
#'
#' @param tumourname Tumour identifier, this is used as a prefix for the output files. If allele counts are supplied separately, they are expected to have this identifier as prefix.
#' @param normalname Matched normal identifier, this is used as a prefix for the output files. If allele counts are supplied separately, they are expected to have this identifier as prefix.
#' @param tumour_data_file A BAM or CEL file for the tumour
#' @param normal_data_file A BAM or CEL file for the normal
#' @param ref_fasta Genome fasta file used for alignment (optional but needed for CRAM support)
#' @param imputeinfofile Full path to a Battenberg impute info file with pointers to Impute2 reference data
#' @param g1000prefix Full prefix path to 1000 Genomes SNP loci data, as part of the Battenberg reference data
#' @param problemloci Full path to a problem loci file that contains SNP loci that should be filtered out
#' @param gccorrectprefix Full prefix path to GC content files, as part of the Battenberg reference data, not required for SNP6 data (Default: NULL)
#' @param repliccorrectprefix Full prefix path to replication timing files, as part of the Battenberg reference data, not required for SNP6 data (Default: NULL)
#' @param g1000allelesprefix Full prefix path to 1000 Genomes SNP alleles data, as part of the Battenberg reference data, not required for SNP6 data (Default: NA)
#' @param ismale A boolean set to TRUE if the donor is male, set to FALSE if female, not required for SNP6 data (Default: NA)
#' @param data_type String that contains either wgs or snp6 depending on the supplied input data (Default: wgs)
#' @param impute_exe Pointer to the Impute2 executable (Default: impute2, i.e. expected in $PATH)
#' @param allelecounter_exe Pointer to the alleleCounter executable (Default: alleleCounter, i.e. expected in $PATH)
#' @param nthreads The number of concurrent processes to use while running the Battenberg pipeline (Default: 8)
#' @param platform_gamma Platform scaling factor, suggestions are set to 1 for wgs and to 0.55 for snp6 (Default: 1)
#' @param phasing_gamma Gamma parameter used when correcting phasing mistakes (Default: 1)
#' @param segmentation_gamma The gamma parameter controls the size of the penalty of starting a new segment during segmentation. It is therefore the key parameter for controlling the number of segments (Default: 10)
#' @param segmentation_kmin Kmin represents the minimum number of probes/SNPs that a segment should consist of (Default: 3)
#' @param phasing_kmin Kmin used when correcting for phasing mistakes (Default: 3)
#' @param clonality_dist_metric Distance metric to use when choosing purity/ploidy combinations (Default: 0)
#' @param ascat_dist_metric Distance metric to use when choosing purity/ploidy combinations (Default: 1)
#' @param min_ploidy Minimum ploidy to be considered (Default: 1.6)
#' @param max_ploidy Maximum ploidy to be considered (Default: 4.8)
#' @param min_rho Minimum purity to be considered (Default: 0.1)
#' @param min_goodness Minimum goodness of fit required for a purity/ploidy combination to be accepted as a solution (Default: 0.63)
#' @param uninformative_BAF_threshold The threshold beyond which BAF becomes uninformative (Default: 0.51)
#' @param min_normal_depth Minimum depth required in the matched normal for a SNP to be considered as part of the wgs analysis (Default: 10)
#' @param min_base_qual Minimum base quality required for a read to be counted when allele counting (Default: 20)
#' @param min_map_qual Minimum mapping quality required for a read to be counted when allele counting (Default: 35)
#' @param calc_seg_baf_option Sets way to calculate BAF per segment: 1=mean, 2=median, 3=ifelse median==0 | 1, mean, median (Default: 3)
#' @param skip_allele_counting Provide TRUE when allele counting can be skipped (i.e. its already done) (Default: FALSE)
#' @param skip_preprocessing Provide TRUE when preprocessing is already complete (Default: FALSE)
#' @param skip_phasing Provide TRUE when phasing is already complete (Default: FALSE)
#' @param snp6_reference_info_file Reference files for the SNP6 pipeline only (Default: NA)
#' @param apt.probeset.genotype.exe Helper tool for extracting data from CEL files, SNP6 pipeline only (Default: apt-probeset-genotype)
#' @param apt.probeset.summarize.exe Helper tool for extracting data from CEL files, SNP6 pipeline only (Default: apt-probeset-summarize)
#' @param norm.geno.clust.exe Helper tool for extracting data from CEL files, SNP6 pipeline only (Default: normalize_affy_geno_cluster.pl)
#' @param birdseed_report_file Sex inference output file, SNP6 pipeline only (Default: birdseed.report.txt)
#' @param heterozygousFilter Legacy option to set a heterozygous SNP filter, SNP6 pipeline only (Default: "none")
#' @param prior_breakpoints_file A two column file with prior breakpoints to be used during segmentation (Default: NULL)
#' @author sd11
#' @export
battenberg = function(tumourname, normalname, tumour_data_file, normal_data_file, imputeinfofile, g1000prefix, problemloci, gccorrectprefix=NULL,
repliccorrectprefix=NULL, g1000allelesprefix=NA, ismale=NA, data_type="wgs", impute_exe="impute2", allelecounter_exe="alleleCounter", nthreads=8, platform_gamma=1, phasing_gamma=1,
segmentation_gamma=10, segmentation_kmin=3, phasing_kmin=1, clonality_dist_metric=0, ascat_dist_metric=1, min_ploidy=1.6,
max_ploidy=4.8, min_rho=min_rho, min_goodness=0.63, uninformative_BAF_threshold=0.51, min_normal_depth=10, min_base_qual=20,
min_map_qual=35, calc_seg_baf_option=3, skip_allele_counting=F, skip_preprocessing=F, skip_phasing=F,
snp6_reference_info_file=NA, apt.probeset.genotype.exe="apt-probeset-genotype", apt.probeset.summarize.exe="apt-probeset-summarize",
norm.geno.clust.exe="normalize_affy_geno_cluster.pl", birdseed_report_file="birdseed.report.txt", heterozygousFilter="none",
prior_breakpoints_file=NULL,chr_prefixed=FALSE,verbose=FALSE,logfile_prefix="./",ref_fasta=NULL) {
requireNamespace("foreach")
requireNamespace("doParallel")
requireNamespace("parallel")
if (data_type=="wgs" & is.na(ismale)) {
stop("Please provide a boolean denominator whether this sample represents a male donor")
}
if (data_type=="wgs" & is.na(g1000allelesprefix)) {
stop("Please provide a path to 1000 Genomes allele reference files")
}
if (data_type=="wgs" & is.null(gccorrectprefix)) {
stop("Please provide a path to GC content reference files")
}
if (!file.exists(problemloci)) {
stop("Please provide a path to a problematic loci file")
}
if (!file.exists(imputeinfofile)) {
stop("Please provide a path to an impute info file")
}
# check whether the impute_info.txt file contains correct paths
check.imputeinfofile(imputeinfofile, ismale)
if (data_type=="wgs" | data_type=="WGS") {
chrom_names = get.chrom.names(imputeinfofile, ismale)
logr_file = paste(tumourname, "_mutantLogR_gcCorrected.tab", sep="")
allelecounts_file = paste(tumourname, "_alleleCounts.tab", sep="")
} else if (data_type=="snp6" | data_type=="SNP6") {
chrom_names = get.chrom.names(imputeinfofile, TRUE)
logr_file = paste(tumourname, "_mutantLogR.tab", sep="")
allelecounts_file = NULL
}
if (!skip_preprocessing) {
if (data_type=="wgs" | data_type=="WGS") {
# Setup for parallel computing
clp = parallel::makeCluster(nthreads)
doParallel::registerDoParallel(clp)
prepare_wgs(chrom_names=chrom_names,
tumourbam=tumour_data_file,
normalbam=normal_data_file,
tumourname=tumourname,
normalname=normalname,
g1000allelesprefix=g1000allelesprefix,
g1000prefix=g1000prefix,
gccorrectprefix=gccorrectprefix,
repliccorrectprefix=repliccorrectprefix,
min_base_qual=min_base_qual,
min_map_qual=min_map_qual,
allelecounter_exe=allelecounter_exe,
min_normal_depth=min_normal_depth,
nthreads=nthreads,
skip_allele_counting=skip_allele_counting,
chr_prefixed=chr_prefixed,verbose=verbose,
ref_fasta = ref_fasta)
# Kill the threads
parallel::stopCluster(clp)
} else if (data_type=="snp6" | data_type=="SNP6") {
prepare_snp6(tumour_cel_file=tumour_data_file,
normal_cel_file=normal_data_file,
tumourname=tumourname,
chrom_names=chrom_names,
snp6_reference_info_file=snp6_reference_info_file,
apt.probeset.genotype.exe=apt.probeset.genotype.exe,
apt.probeset.summarize.exe=apt.probeset.summarize.exe,
norm.geno.clust.exe=norm.geno.clust.exe,
birdseed_report_file=birdseed_report_file)
} else {
print("Unknown data type provided, please provide wgs or snp6")
q(save="no", status=1)
}
}
if (data_type=="snp6" | data_type=="SNP6") {
# Infer what the gender is - WGS requires it to be specified
gender = infer_gender_birdseed(birdseed_report_file)
ismale = gender == "male"
}
if (!skip_phasing) {
# Setup for parallel computing
clp = parallel::makeCluster(nthreads)
doParallel::registerDoParallel(clp)
foreach::foreach (chrom=1:length(chrom_names)) %dopar% {
#switch to non-parallel for full verbose debugging mode
#for(chrom in 1:length(chrom_names)){
run_haplotyping(chrom=chrom,
tumourname=tumourname,
normalname=normalname,
ismale=ismale,
imputeinfofile=imputeinfofile,
problemloci=problemloci,
impute_exe=impute_exe,
min_normal_depth=min_normal_depth,
chrom_names=chrom_names,
snp6_reference_info_file=snp6_reference_info_file,
heterozygousFilter=heterozygousFilter,
chr_prefixed=chr_prefixed,
logfile_prefix=logfile_prefix)
}
# Kill the threads as from here its all single core
parallel::stopCluster(clp)
# Combine all the BAF output into a single file
combine.baf.files(inputfile.prefix=paste(tumourname, "_chr", sep=""),
inputfile.postfix="_heterozygousMutBAFs_haplotyped.txt",
outputfile=paste(tumourname, "_heterozygousMutBAFs_haplotyped.txt", sep=""),
no.chrs=length(chrom_names))
}
# Segment the phased and haplotyped BAF data
segment.baf.phased(samplename=tumourname,
inputfile=paste(tumourname, "_heterozygousMutBAFs_haplotyped.txt", sep=""),
outputfile=paste(tumourname, ".BAFsegmented.txt", sep=""),
prior_breakpoints_file=prior_breakpoints_file,
gamma=segmentation_gamma,
phasegamma=phasing_gamma,
kmin=segmentation_kmin,
phasekmin=phasing_kmin,
calc_seg_baf_option=calc_seg_baf_option,
chr_prefixed=chr_prefixed)
# Fit a clonal copy number profile
fit.copy.number(samplename=tumourname,
outputfile.prefix=paste(tumourname, "_", sep=""),
inputfile.baf.segmented=paste(tumourname, ".BAFsegmented.txt", sep=""),
inputfile.baf=paste(tumourname,"_mutantBAF.tab", sep=""),
inputfile.logr=logr_file,
dist_choice=clonality_dist_metric,
ascat_dist_choice=ascat_dist_metric,
min.ploidy=min_ploidy,
max.ploidy=max_ploidy,
min.rho=min_rho,
min.goodness=min_goodness,
uninformative_BAF_threshold=uninformative_BAF_threshold,
gamma_param=platform_gamma,
use_preset_rho_psi=F,
preset_rho=NA,
preset_psi=NA,
read_depth=30)
# Go over all segments, determine which segements are a mixture of two states and fit a second CN state
if(chr_prefixed){
fig_prefix = "_subclones_"
}else{
fig_prefix = "_subclones_chr"
}
callSubclones(sample.name=tumourname,
baf.segmented.file=paste(tumourname, ".BAFsegmented.txt", sep=""),
logr.file=logr_file,
rho.psi.file=paste(tumourname, "_rho_and_psi.txt",sep=""),
output.file=paste(tumourname,"_subclones.txt", sep=""),
output.figures.prefix=paste(tumourname,fig_prefix, sep=""),
output.gw.figures.prefix=paste(tumourname,"_BattenbergProfile", sep=""),
masking_output_file=paste(tumourname, "_segment_masking_details.txt", sep=""),
prior_breakpoints_file=prior_breakpoints_file,
chr_names=chrom_names,
gamma=platform_gamma,
segmentation.gamma=NA,
siglevel=0.05,
maxdist=0.01,
noperms=1000,
calc_seg_baf_option=calc_seg_baf_option)
# Make some post-hoc plots
make_posthoc_plots(samplename=tumourname,
logr_file=logr_file,
subclones_file=paste(tumourname, "_subclones.txt", sep=""),
rho_psi_file=paste(tumourname, "_rho_and_psi.txt", sep=""),
bafsegmented_file=paste(tumourname, ".BAFsegmented.txt", sep=""),
logrsegmented_file=paste(tumourname, ".logRsegmented.txt", sep=""),
allelecounts_file=allelecounts_file)
# Save refit suggestions for a future rerun
cnfit_to_refit_suggestions(samplename=tumourname,
subclones_file=paste(tumourname, "_subclones.txt", sep=""),
rho_psi_file=paste(tumourname, "_rho_and_psi.txt", sep=""),
gamma_param=platform_gamma)
}
shaghayeghsoudi/Battenberg_customized documentation built on Feb. 13, 2022, 4:10 a.m.
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Defines functions battenberg
Documented in battenberg
#' Run the Battenberg pipeline
#'
#' @param tumourname Tumour identifier, this is used as a prefix for the output files. If allele counts are supplied separately, they are expected to have this identifier as prefix.
#' @param normalname Matched normal identifier, this is used as a prefix for the output files. If allele counts are supplied separately, they are expected to have this identifier as prefix.
#' @param tumour_data_file A BAM or CEL file for the tumour
#' @param normal_data_file A BAM or CEL file for the normal
#' @param ref_fasta Genome fasta file used for alignment (optional but needed for CRAM support)
#' @param imputeinfofile Full path to a Battenberg impute info file with pointers to Impute2 reference data
#' @param g1000prefix Full prefix path to 1000 Genomes SNP loci data, as part of the Battenberg reference data
#' @param problemloci Full path to a problem loci file that contains SNP loci that should be filtered out
#' @param gccorrectprefix Full prefix path to GC content files, as part of the Battenberg reference data, not required for SNP6 data (Default: NULL)
#' @param repliccorrectprefix Full prefix path to replication timing files, as part of the Battenberg reference data, not required for SNP6 data (Default: NULL)
#' @param g1000allelesprefix Full prefix path to 1000 Genomes SNP alleles data, as part of the Battenberg reference data, not required for SNP6 data (Default: NA)
#' @param ismale A boolean set to TRUE if the donor is male, set to FALSE if female, not required for SNP6 data (Default: NA)
#' @param data_type String that contains either wgs or snp6 depending on the supplied input data (Default: wgs)
#' @param impute_exe Pointer to the Impute2 executable (Default: impute2, i.e. expected in $PATH)
#' @param allelecounter_exe Pointer to the alleleCounter executable (Default: alleleCounter, i.e. expected in $PATH)
#' @param nthreads The number of concurrent processes to use while running the Battenberg pipeline (Default: 8)
#' @param platform_gamma Platform scaling factor, suggestions are set to 1 for wgs and to 0.55 for snp6 (Default: 1)
#' @param phasing_gamma Gamma parameter used when correcting phasing mistakes (Default: 1)
#' @param segmentation_gamma The gamma parameter controls the size of the penalty of starting a new segment during segmentation. It is therefore the key parameter for controlling the number of segments (Default: 10)
#' @param segmentation_kmin Kmin represents the minimum number of probes/SNPs that a segment should consist of (Default: 3)
#' @param phasing_kmin Kmin used when correcting for phasing mistakes (Default: 3)
#' @param clonality_dist_metric Distance metric to use when choosing purity/ploidy combinations (Default: 0)
#' @param ascat_dist_metric Distance metric to use when choosing purity/ploidy combinations (Default: 1)
#' @param min_ploidy Minimum ploidy to be considered (Default: 1.6)
#' @param max_ploidy Maximum ploidy to be considered (Default: 4.8)
#' @param min_rho Minimum purity to be considered (Default: 0.1)
#' @param min_goodness Minimum goodness of fit required for a purity/ploidy combination to be accepted as a solution (Default: 0.63)
#' @param uninformative_BAF_threshold The threshold beyond which BAF becomes uninformative (Default: 0.51)
#' @param min_normal_depth Minimum depth required in the matched normal for a SNP to be considered as part of the wgs analysis (Default: 10)
#' @param min_base_qual Minimum base quality required for a read to be counted when allele counting (Default: 20)
#' @param min_map_qual Minimum mapping quality required for a read to be counted when allele counting (Default: 35)
#' @param calc_seg_baf_option Sets way to calculate BAF per segment: 1=mean, 2=median, 3=ifelse median==0 | 1, mean, median (Default: 3)
#' @param skip_allele_counting Provide TRUE when allele counting can be skipped (i.e. its already done) (Default: FALSE)
#' @param skip_preprocessing Provide TRUE when preprocessing is already complete (Default: FALSE)
#' @param skip_phasing Provide TRUE when phasing is already complete (Default: FALSE)
#' @param snp6_reference_info_file Reference files for the SNP6 pipeline only (Default: NA)
#' @param apt.probeset.genotype.exe Helper tool for extracting data from CEL files, SNP6 pipeline only (Default: apt-probeset-genotype)
#' @param apt.probeset.summarize.exe Helper tool for extracting data from CEL files, SNP6 pipeline only (Default: apt-probeset-summarize)
#' @param norm.geno.clust.exe Helper tool for extracting data from CEL files, SNP6 pipeline only (Default: normalize_affy_geno_cluster.pl)
#' @param birdseed_report_file Sex inference output file, SNP6 pipeline only (Default: birdseed.report.txt)
#' @param heterozygousFilter Legacy option to set a heterozygous SNP filter, SNP6 pipeline only (Default: "none")
#' @param prior_breakpoints_file A two column file with prior breakpoints to be used during segmentation (Default: NULL)
#' @author sd11
#' @export
battenberg = function(tumourname, normalname, tumour_data_file, normal_data_file, imputeinfofile, g1000prefix, problemloci, gccorrectprefix=NULL,
repliccorrectprefix=NULL, g1000allelesprefix=NA, ismale=NA, data_type="wgs", impute_exe="impute2", allelecounter_exe="alleleCounter", nthreads=8, platform_gamma=1, phasing_gamma=1,
segmentation_gamma=10, segmentation_kmin=3, phasing_kmin=1, clonality_dist_metric=0, ascat_dist_metric=1, min_ploidy=1.6,
max_ploidy=4.8, min_rho=min_rho, min_goodness=0.63, uninformative_BAF_threshold=0.51, min_normal_depth=10, min_base_qual=20,
min_map_qual=35, calc_seg_baf_option=3, skip_allele_counting=F, skip_preprocessing=F, skip_phasing=F,
snp6_reference_info_file=NA, apt.probeset.genotype.exe="apt-probeset-genotype", apt.probeset.summarize.exe="apt-probeset-summarize",
norm.geno.clust.exe="normalize_affy_geno_cluster.pl", birdseed_report_file="birdseed.report.txt", heterozygousFilter="none",
prior_breakpoints_file=NULL,chr_prefixed=FALSE,verbose=FALSE,logfile_prefix="./",ref_fasta=NULL) {
requireNamespace("foreach")
requireNamespace("doParallel")
requireNamespace("parallel")
if (data_type=="wgs" & is.na(ismale)) {
stop("Please provide a boolean denominator whether this sample represents a male donor")
}
if (data_type=="wgs" & is.na(g1000allelesprefix)) {
stop("Please provide a path to 1000 Genomes allele reference files")
}
if (data_type=="wgs" & is.null(gccorrectprefix)) {
stop("Please provide a path to GC content reference files")
}
if (!file.exists(problemloci)) {
stop("Please provide a path to a problematic loci file")
}
if (!file.exists(imputeinfofile)) {
stop("Please provide a path to an impute info file")
}
# check whether the impute_info.txt file contains correct paths
check.imputeinfofile(imputeinfofile, ismale)
if (data_type=="wgs" | data_type=="WGS") {
chrom_names = get.chrom.names(imputeinfofile, ismale)
logr_file = paste(tumourname, "_mutantLogR_gcCorrected.tab", sep="")
allelecounts_file = paste(tumourname, "_alleleCounts.tab", sep="")
} else if (data_type=="snp6" | data_type=="SNP6") {
chrom_names = get.chrom.names(imputeinfofile, TRUE)
logr_file = paste(tumourname, "_mutantLogR.tab", sep="")
allelecounts_file = NULL
}
if (!skip_preprocessing) {
if (data_type=="wgs" | data_type=="WGS") {
# Setup for parallel computing
clp = parallel::makeCluster(nthreads)
doParallel::registerDoParallel(clp)
prepare_wgs(chrom_names=chrom_names,
tumourbam=tumour_data_file,
normalbam=normal_data_file,
tumourname=tumourname,
normalname=normalname,
g1000allelesprefix=g1000allelesprefix,
g1000prefix=g1000prefix,
gccorrectprefix=gccorrectprefix,
repliccorrectprefix=repliccorrectprefix,
min_base_qual=min_base_qual,
min_map_qual=min_map_qual,
allelecounter_exe=allelecounter_exe,
min_normal_depth=min_normal_depth,
nthreads=nthreads,
skip_allele_counting=skip_allele_counting,
chr_prefixed=chr_prefixed,verbose=verbose,
ref_fasta = ref_fasta)
# Kill the threads
parallel::stopCluster(clp)
} else if (data_type=="snp6" | data_type=="SNP6") {
prepare_snp6(tumour_cel_file=tumour_data_file,
normal_cel_file=normal_data_file,
tumourname=tumourname,
chrom_names=chrom_names,
snp6_reference_info_file=snp6_reference_info_file,
apt.probeset.genotype.exe=apt.probeset.genotype.exe,
apt.probeset.summarize.exe=apt.probeset.summarize.exe,
norm.geno.clust.exe=norm.geno.clust.exe,
birdseed_report_file=birdseed_report_file)
} else {
print("Unknown data type provided, please provide wgs or snp6")
q(save="no", status=1)
}
}
if (data_type=="snp6" | data_type=="SNP6") {
# Infer what the gender is - WGS requires it to be specified
gender = infer_gender_birdseed(birdseed_report_file)
ismale = gender == "male"
}
if (!skip_phasing) {
# Setup for parallel computing
clp = parallel::makeCluster(nthreads)
doParallel::registerDoParallel(clp)
foreach::foreach (chrom=1:length(chrom_names)) %dopar% {
#switch to non-parallel for full verbose debugging mode
#for(chrom in 1:length(chrom_names)){
run_haplotyping(chrom=chrom,
tumourname=tumourname,
normalname=normalname,
ismale=ismale,
imputeinfofile=imputeinfofile,
problemloci=problemloci,
impute_exe=impute_exe,
min_normal_depth=min_normal_depth,
chrom_names=chrom_names,
snp6_reference_info_file=snp6_reference_info_file,
heterozygousFilter=heterozygousFilter,
chr_prefixed=chr_prefixed,
logfile_prefix=logfile_prefix)
}
# Kill the threads as from here its all single core
parallel::stopCluster(clp)
# Combine all the BAF output into a single file
combine.baf.files(inputfile.prefix=paste(tumourname, "_chr", sep=""),
inputfile.postfix="_heterozygousMutBAFs_haplotyped.txt",
outputfile=paste(tumourname, "_heterozygousMutBAFs_haplotyped.txt", sep=""),
no.chrs=length(chrom_names))
}
# Segment the phased and haplotyped BAF data
segment.baf.phased(samplename=tumourname,
inputfile=paste(tumourname, "_heterozygousMutBAFs_haplotyped.txt", sep=""),
outputfile=paste(tumourname, ".BAFsegmented.txt", sep=""),
prior_breakpoints_file=prior_breakpoints_file,
gamma=segmentation_gamma,
phasegamma=phasing_gamma,
kmin=segmentation_kmin,
phasekmin=phasing_kmin,
calc_seg_baf_option=calc_seg_baf_option,
chr_prefixed=chr_prefixed)
# Fit a clonal copy number profile
fit.copy.number(samplename=tumourname,
outputfile.prefix=paste(tumourname, "_", sep=""),
inputfile.baf.segmented=paste(tumourname, ".BAFsegmented.txt", sep=""),
inputfile.baf=paste(tumourname,"_mutantBAF.tab", sep=""),
inputfile.logr=logr_file,
dist_choice=clonality_dist_metric,
ascat_dist_choice=ascat_dist_metric,
min.ploidy=min_ploidy,
max.ploidy=max_ploidy,
min.rho=min_rho,
min.goodness=min_goodness,
uninformative_BAF_threshold=uninformative_BAF_threshold,
gamma_param=platform_gamma,
use_preset_rho_psi=F,
preset_rho=NA,
preset_psi=NA,
read_depth=30)
# Go over all segments, determine which segements are a mixture of two states and fit a second CN state
if(chr_prefixed){
fig_prefix = "_subclones_"
}else{
fig_prefix = "_subclones_chr"
}
callSubclones(sample.name=tumourname,
baf.segmented.file=paste(tumourname, ".BAFsegmented.txt", sep=""),
logr.file=logr_file,
rho.psi.file=paste(tumourname, "_rho_and_psi.txt",sep=""),
output.file=paste(tumourname,"_subclones.txt", sep=""),
output.figures.prefix=paste(tumourname,fig_prefix, sep=""),
output.gw.figures.prefix=paste(tumourname,"_BattenbergProfile", sep=""),
masking_output_file=paste(tumourname, "_segment_masking_details.txt", sep=""),
prior_breakpoints_file=prior_breakpoints_file,
chr_names=chrom_names,
gamma=platform_gamma,
segmentation.gamma=NA,
siglevel=0.05,
maxdist=0.01,
noperms=1000,
calc_seg_baf_option=calc_seg_baf_option)
# Make some post-hoc plots
make_posthoc_plots(samplename=tumourname,
logr_file=logr_file,
subclones_file=paste(tumourname, "_subclones.txt", sep=""),
rho_psi_file=paste(tumourname, "_rho_and_psi.txt", sep=""),
bafsegmented_file=paste(tumourname, ".BAFsegmented.txt", sep=""),
logrsegmented_file=paste(tumourname, ".logRsegmented.txt", sep=""),
allelecounts_file=allelecounts_file)
# Save refit suggestions for a future rerun
cnfit_to_refit_suggestions(samplename=tumourname,
subclones_file=paste(tumourname, "_subclones.txt", sep=""),
rho_psi_file=paste(tumourname, "_rho_and_psi.txt", sep=""),
gamma_param=platform_gamma)
}
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