plotCDS {riboSeqR} | R Documentation |
For each sample, the average (normalised by translation abundance over transcript) of the ribosome footprints of a given length alignments at the 5' and 3' ends of all specified transcripts beginning at each base relative to coding start/end are plotted. The bases are colour coded relative to start codon.
plotCDS(coordinates, riboDat, lengths = 27, min5p = -20, max5p = 200, min3p = -200, max3p = 20, cap, main = "", plot = TRUE, ...)
coordinates |
Coordinates (as a |
riboDat |
|
lengths |
Lengths of footprints to be plotted. May be given as a vector, in which case multiple plots will be produced. |
min5p |
The distance upstream of the translation start to be plotted. |
max5p |
The distance downstream of the translation start to be plotted. |
min3p |
The distance upstream of the translation end to be plotted. |
max3p |
The distance downstream of the translation end to be plotted. |
cap |
If given, caps the height of plotted values. |
main |
Title of the plot. |
plot |
Should the acquired matrix of mean expression be plotted? Defaults to TRUE. |
... |
Additional arguments to be passed to 'plot' and 'axes'. |
Invisibly returns lists of lists of matrices containing weighted averages plotted for each sample/length combination.
Thomas J. Hardcastle
#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(0, 2), hitMean = 50, unqhitMean = 10, fS = fS) plotCDS(coordinates = ffCs@CDS, riboDat = riboDat, lengths = 27)