readCounts {ASpli} | R Documentation |
Summarize read overlaps against all feature levels
readCounts( features, bam, targets, cores = 1, readLength, maxISize, minAnchor = 10)
features |
An object of class ASpliFeatures. It is a list of GRanges at gene, bin and junction level |
bam |
List of GAlignments objects corresponding to bam files of samples. |
targets |
A dataframe containing sample, bam and experimental factors columns |
readLength |
Read length of sequenced library. It is used for compute E1I and IE2 read summarization |
maxISize |
maximum intron expected size. Junctions longer than this size will be dicarded |
cores |
Number of cores to use. Default is 1 |
minAnchor |
Minimum percentage of read that should be aligned to an exon-intron boundary |
An object of class ASpliCounts. Each slot is a dataframe containing features metadata and read counts. Summarization is reported at gene, bin, junction and intron flanking regions (E1I, IE2).
Estefania Mancini, Javier Iserte, Marcelo Yanovsky, Ariel Chernomoretz
Accesors: countsg
,
countsb
,
countsj
,
countse1i
,
countsie2
,
rdsg
,
rdsb
,
Export: writeCounts
# Create a transcript DB from gff/gtf annotation file. # Warnings in this examples can be ignored. library(GenomicFeatures) genomeTxDb <- makeTxDbFromGFF( system.file('extdata','genes.mini.gtf', package="ASpli") ) # Create an ASpliFeatures object from TxDb features <- binGenome( genomeTxDb ) # Define bam files, sample names and experimental factors for targets. bamFileNames <- c( "A_C_0.bam", "A_C_1.bam", "A_C_2.bam", "A_D_0.bam", "A_D_1.bam", "A_D_2.bam" ) targets <- data.frame( row.names = paste0('Sample_',c(1:6)), bam = system.file( 'extdata', bamFileNames, package="ASpli" ), factor1 = c( 'C','C','C','D','D','D') ) # Load reads from bam files bams <- loadBAM( targets ) # Read counts from bam files counts <- readCounts( features, bams, targets, cores = 1, readLength = 100, maxISize = 50000 ) # Export data writeCounts( counts, output.dir = "only_counts" )