codonInfo: Associates the read counts on codons with the codon type for...

In RiboProfiling: Ribosome Profiling Data Analysis: from BAM to Data Representation and Interpretation

Description

Associates the read counts on codons with the codon type for each ORF.

Usage

codonInfo(listReadsCodon, genomeSeq, orfCoord, motifSize)

Arguments

listReadsCodon	a list of data.frame objects. It contains the number of reads per codon in a CDS.
genomeSeq	a BSgenome object. It contains the full genome sequences for the organism.
orfCoord	a GRangesList. The coordinates of the ORFs on the genome.
motifSize	an integer. The number of nucleotides in each motif on which to compute coverage and usage. Either 3, 6, or 9. Default 3 nucleotides (codon). Attention! For long motifs, the function can be quite slow!!

Value

a list of 2 data.frame objects: one with the number of times each codon type is found in each ORF and one with the number of reads for each codon type in each ORF.

Examples

#for each codon in each ORF get the read coverage
#parameter listReadsCodon can be returned by the riboSeqFromBam function
#it corresponts to the 2nd element in the list returned by riboSeqFromBam
data(codonIndexCovCtrl)
listReadsCodon <- codonIndexCovCtrl

txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene::TxDb.Hsapiens.UCSC.hg19.knownGene

#get the names of the ORFs
#grouped by transcript
cds <- GenomicFeatures::cdsBy(txdb, use.names=TRUE)
orfCoord <- cds[names(cds) %in% names(listReadsCodon)]

#get the genome, please check that the genome has the same seqlevels
genomeSeq <- BSgenome.Hsapiens.UCSC.hg19::BSgenome.Hsapiens.UCSC.hg19
#if not rename it
#gSeq <- GenomeInfoDb::renameSeqlevels(genomeSeq,
#sub("chr", "", GenomeInfoDb::seqlevels(genomeSeq)))

#codon frequency, coverage, and annotation
codonData <- codonInfo(listReadsCodon, genomeSeq, orfCoord)

RiboProfiling documentation built on Nov. 8, 2020, 5:26 p.m.