transcriptWindow {ORFik} | R Documentation |
Gives you binned meta coverage plots, either saved seperatly or all in one.
transcriptWindow( leaders, cds, trailers, df, outdir = NULL, scores = c("sum", "transcriptNormalized"), allTogether = TRUE, colors = experiment.colors(df), title = "Coverage metaplot", windowSize = min(100, min(widthPerGroup(leaders, FALSE)), min(widthPerGroup(cds, FALSE)), min(widthPerGroup(trailers, FALSE))), returnPlot = is.null(outdir), dfr = NULL, idName = "", plot.ext = ".pdf", type = "ofst", is.sorted = FALSE, drop.zero.dt = TRUE, BPPARAM = bpparam() )
leaders |
a |
cds |
a |
trailers |
a |
df |
an ORFik |
outdir |
directory to save to (default: NULL, no saving) |
scores |
scoring function (default: c("sum", "transcriptNormalized")), see ?coverageScorings for possible scores. |
allTogether |
plot all coverage plots in 1 output? (defualt: TRUE) |
colors |
Which colors to use, default auto color from function
|
title |
title of ggplot |
windowSize |
size of binned windows, default: 100 |
returnPlot |
return plot from function, default is.null(outdir), so TRUE if outdir is not defined. |
dfr |
an ORFik |
idName |
A character ID to add to saved name of plot, if you make several plots in the same folder, and same experiment, like splitting transcripts in two groups like targets / nontargets etc. (default: "") |
plot.ext |
character, default: ".pdf". Alternatives: ".png" or ".jpg". |
type |
a character(default: "bedoc"), load files in experiment or some precomputed variant, either "bedo", "bedoc", "pshifted" or default. These are made with ORFik:::simpleLibs(), shiftFootprintsByExperiment().. Will load default if bedoc is not found |
is.sorted |
logical (FALSE), is grl sorted. That is + strand groups in increasing ranges (1,2,3), and - strand groups in decreasing ranges (3,2,1) |
drop.zero.dt |
logical FALSE, if TRUE and as.data.table is TRUE, remove all 0 count positions. This greatly speeds up and most importantly, greatly reduces memory usage. Will not change any plots, unless 0 positions are used in some sense. (mean, median, zscore coverage will only scale differently) |
BPPARAM |
how many cores/threads to use? default: bpparam() |
NULL, or ggplot object if returnPlot is TRUE
Other experiment plots:
transcriptWindow1()
,
transcriptWindowPer()
df <- ORFik.template.experiment()[3,] # Only third library loadRegions(df) # Load leader, cds and trailers as GRangesList #transcriptWindow(leaders, cds, trailers, df, outdir = "directory/to/save")