Description Usage Arguments Value Author(s) Examples
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.
1 2 |
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | #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)
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