shiftPlots | R Documentation |
Around CDS TISs, plot coverage. A good validation for you p-shifting, to see shifts are corresponding and close to the CDS TIS.
shiftPlots(
df,
output = NULL,
title = "Ribo-seq",
scoring = "transcriptNormalized",
pShifted = TRUE,
upstream = if (pShifted) 5 else 20,
downstream = if (pShifted) 20 else 5,
type = "bar",
addFracPlot = TRUE,
plot.ext = ".pdf",
dpi = ifelse(nrow(df) < 22, 300, 200),
height_scaler = ifelse(type == "heatmap", 85, 95),
BPPARAM = bpparam()
)
df |
an ORFik |
output |
name to save file, full path. (Default NULL) No saving. Sett to "auto" to save to QC_STATS folder of experiment named: "pshifts_barplots.png" or "pshifts_heatmaps.png" depending on type argument. Folder must exist! |
title |
Title for top of plot, default "Ribo-seq". A more informative name could be "Ribo-seq zebrafish Chew et al. 2013" |
scoring |
which scoring scheme to use for heatmap, default "transcriptNormalized". Some alternatives: "sum", "zscore". |
pShifted |
a logical (TRUE), are Ribo-seq reads p-shifted to size 1 width reads? If upstream and downstream is set, this argument is irrelevant. So set to FALSE if this is not p-shifted Ribo-seq. |
upstream |
an integer (5), relative region to get upstream from. Default:
|
downstream |
an integer (20), relative region to get downstream from. Default:
|
type |
character, default "bar". Plot as faceted bars, gives more detailed information of read lengths, but harder to see patterns over multiple read lengths. Alternative: "heatmap", better overview of patterns over multiple read lengths. |
addFracPlot |
logical, default TRUE, add positional sum plot on top per heatmap. |
plot.ext |
default ".pdf". Alternative ".png". Only added if output is "auto". |
dpi |
numeric, default: ifelse(nrow(df) < 22, 300, 200) |
height_scaler |
numeric default: ifelse(type == "heatmap", 85, 95).
The total height of plot in unit "mm" is
|
BPPARAM |
how many cores/threads to use? default: bpparam() |
a ggplot2 grob object
Other pshifting:
changePointAnalysis()
,
detectRibosomeShifts()
,
shiftFootprints()
,
shiftFootprintsByExperiment()
,
shifts_load()
,
shifts_save()
df <- ORFik.template.experiment.zf()
df <- df[df$libtype == "RFP",][1,] #lets only p-shift first RFP sample
#shiftFootprintsByExperiment(df, output_format = "bedo)
#grob <- shiftPlots(df, title = "Ribo-seq Human ORFik et al. 2020")
#plot(grob) #Only plot in RStudio for small amount of files!
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