mergePerGroup {BaalChIP} | R Documentation |
Method mergePerGroup
Merges all ChIP-seq datasets within a group of samples creating a data.frame that contains allele-specific read count data for all variants that need to be analysed.
mergePerGroup(.Object) ## S4 method for signature 'BaalChIP' mergePerGroup(.Object)
.Object |
An object of the |
if QCfilter has been applied, will use the most up-to-date variant set available for each individual BAM file (after QC). Missing values are allowed for heterozygous variants that are not available (e.g. do not pass filter for a particular ChIP-seq dataset).
An updated BaalChIP
object with the slot mergedCounts
containing a data.frame of merged samples per group.
Ines de Santiago
BaalChIP.get
, plotQC
, summaryQC
setwd(system.file('test',package='BaalChIP')) samplesheet <- 'exampleChIP.tsv' hets <- c('MCF7'='MCF7_hetSNP.txt', 'GM12891'='GM12891_hetSNP.txt') res <- BaalChIP(samplesheet=samplesheet, hets=hets) res <- alleleCounts(res, min_base_quality=10, min_mapq=15) data('blacklist_hg19') data('pickrell2011cov1_hg19') data('UniqueMappability50bp_hg19') res <- QCfilter(res, RegionsToFilter=list('blacklist'=blacklist_hg19, 'highcoverage'=pickrell2011cov1_hg19), RegionsToKeep=list('UniqueMappability'=UniqueMappability50bp_hg19)) res <- mergePerGroup(res) #retrieve mergedCounts: counts <- BaalChIP.get(res, 'mergedCounts') #mergedCounts are grouped by group_name: names(counts) sapply(counts, dim) #check out the result for one of the groups: head(counts[[1]])