Extracts mRNA counts from a riboDat object for a set of coding sequence coordinates.

Description

Takes mRNA count data from riboDat object, maps them to coding sequences specified in GRanges object, and counts the total number of hits. This is a crude approach intended to quickly produce comparable data to ribosome footprint counts. More sophisticated alternatives, addressing coverage variation, isoforms, multireads &c. have been widely described in the literature on mRNA-seq analyses.

Usage

rnaCounts(riboDat, CDS)

Arguments

Details

The count data thus acquired can be compared to counts of ribosomal footprint data through a beta-binomial analysis (see vignette) to discover differential translation.

Value

A matrix containing count data for the RNA-seq libraries.

Author(s)

Thomas J. Hardcastle

See Also

sliceCounts

Examples

#ribosomal footprint data
datadir <- system.file("extdata", package = "riboSeqR")
ribofiles <- paste(datadir, 
                   "/chlamy236_plus_deNovo_plusOnly_Index", c(17,3,5,7), sep = "")
rnafiles <- paste(datadir, 
                  "/chlamy236_plus_deNovo_plusOnly_Index", c(10,12,14,16), sep = "")

riboDat <- readRibodata(ribofiles, rnafiles, replicates = c("WT", "WT",
"M", "M")) 

# CDS coordinates
chlamyFasta <- paste(datadir, "/rsem_chlamy236_deNovo.transcripts.fa", sep = "")
fastaCDS <- findCDS(fastaFile = chlamyFasta, 
                    startCodon = c("ATG"), 
                    stopCodon = c("TAG", "TAA", "TGA"))

# frame calling
fCs <- frameCounting(riboDat, fastaCDS)

# analysis of frame shift for 27 and 28-mers.
fS <- readingFrame(rC = fCs, lengths = 27:28)

# filter coding sequences. 27-mers are principally in the 1-frame,
# 28-mers are principally in the 0-frame relative to coding start (see
# readingFrame function).

ffCs <- filterHits(fCs, lengths = c(27, 28), frames = list(1, 0), 
                   hitMean = 50, unqhitMean = 10, fS = fS)

# Extract counts of RNA hits from riboCount data.
rnaCounts <- rnaCounts(riboDat, ffCs@CDS)