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caRpools (version 0.83)

carpools.hit.overview: Analysis: Analysis of pooled CRISPR screening data using a Wilcoxon Test

Description

Candidate genes from all methods can be plotted in an overview to identify overlapping signficant candidate genes using `carpools.hit.overview`.

Usage

carpools.hit.overview(wilcox=NULL, deseq=NULL, mageck=NULL, cutoff.deseq = 0.001, cutoff.wilcox = 0.05, cutoff.mageck = 0.05, cutoff.override=FALSE, cutoff.hits=NULL, plot.genes="overlapping", type="all")

Arguments

wilcox
Data output from `stat.wilcox`. *Default* NULL *Values* Data output from `stat.wilcox`.
deseq
Data output from `stat.deseq`. *Default* NULL *Values* Data output from `stat.deseq`.
mageck
Data output from `stat.mageck`. *Default* NULL *Values* Data output from `stat.mageck`.
cutoff.deseq
P-Value threshold used to determine significance. *Default* 0.001 *Values* numeric
cutoff.wilcox
P-Value threshold used to determine significance. *Default* 0.001 *Values* numeric
cutoff.mageck
P-Value threshold used to determine significance. *Default* 0.001 *Values* numeric
cutoff.override
Shall the p-value threshold be ignored? If this is TRUE, the top percentage gene of `cutoff.hits` is used instead. *Default* FALSE *Values* TRUE, FALSE
cutoff.hits
The percentatge of top genes being used if `cutoff.override=TRUE`. *Default** NULL *Values* numeric
plot.genes
Defines what kind of data is used. By default, overlapping genes are highlighted in red color. *Default* "overlapping" *Values* "overlapping"
type
Defines whether all genes are plotted or only those being enriched or depleted. *Default* "all" *Values* "all", "enriched", "depleted"

Value

Returns a generic plot.

Details

none

Examples

Run this code
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)

carpools.hit.overview(wilcox=data.wilcox, deseq=data.deseq, mageck=data.mageck,
    cutoff.deseq = 0.001, cutoff.wilcox = 0.05, cutoff.mageck = 0.05,
    cutoff.override=FALSE, cutoff.hits=NULL, plot.genes="overlapping", type="enriched")

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