Description Usage Arguments Details Value Note Author(s) Examples
The output from 'stat.wilcox', 'stat.DEseq' and 'stat.mageck' can be visualized with 'carpools.hitident'. In this case, log2 fold changes are plotted against the gene names for all methods as well as the number of significant sgRNAs for data analyzed with DESeq2 or MAGeCK.
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data |
Output data from either 'stat.wilcox', 'stat.DEseq' or 'stat.mageck'. *Default* empty *Values* Output from either 'stat.wilcox', 'stat.DEseq' or 'stat.mageck'. |
type |
Which type of analysis method was used? *Default* deseq2 *Values* "wilcox", "deseq2", "mageck" |
title |
Title of the plot. *Default* "DESeq2 plot" *Values* (character) |
print.names |
Shall the names of significant or top candidates being plotted? *Default* FALSE *Values* TRUE, FALSE (boolean) |
cutoff |
A vector containing plotting cutoffs if 'print.names=TRUE'. c("top enriched", "top depleted", "most sgRNA enriched", "most sgRNA depleted"). *Default* c(0,0,0,0) *Values* Vector of length 4 (numeric) |
inches |
see '?par'. *Default* 0.1 *Values* (numeric) |
offsetplot |
Multiplication factor for stretching the plotting area to get a better plot experience. *Default* 1.2 *Values* > 1 (numeric) |
plot.p |
Which p-value shall be plotted and used for visualization? *Default* 0.05 *Values* (numeric) |
sgRNA.top |
For sgRNA plots, this indicates how many genes will be labeled (the top X genes). *Default* 1 *Values* (numeric, integer) |
separate |
Gene that showed enrichment can be plotted separately from those that have shown a depletion for better overview, works only for wilcox. *Default* FALSE *Values* TRUE, FALSE |
none
carpools.hitident returns a generic plot, which can be passed on to any device.
see ?plot for detailed plotting information.
Jan Winter
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 | data(caRpools)
data.wilcox = stat.wilcox(untreated.list = list(CONTROL1, CONTROL2),
treated.list = list(TREAT1,TREAT2), namecolumn=1, fullmatchcolumn=2,
normalize=TRUE, norm.fun=median, sorting=FALSE, controls="random",
control.picks=NULL)
data.deseq = stat.DESeq(untreated.list = list(CONTROL1, CONTROL2),
treated.list = list(TREAT1,TREAT2), namecolumn=1,
fullmatchcolumn=2, extractpattern=expression("^(.+?)(_.+)"),
sorting=FALSE, filename.deseq = "ANALYSIS-DESeq2-sgRNA.tab",
fitType="parametric")
data.mageck = stat.mageck(untreated.list = list(CONTROL1, CONTROL2),
treated.list = list(TREAT1,TREAT2), namecolumn=1, fullmatchcolumn=2,
norm.fun="median", extractpattern=expression("^(.+?)(_.+)"),
mageckfolder=NULL, sort.criteria="neg", adjust.method="fdr",
filename = "TEST" , fdr.pval = 0.05)
mageck.result = carpools.hitident(data.mageck, type="mageck",
title="MAGeCK", inches=0.1, print.names=TRUE, plot.p=0.05, offsetplot=1.2, sgRNA.top=1)
wilcox.result = carpools.hitident(data.wilcox, type="wilcox",
title="Wilcox", inches=0.1, print.names=TRUE, plot.p=0.05, offsetplot=1.2, sgRNA.top=1)
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