caRpools (version 0.83)

carpools.hit.sgrna: Plotting sgRNA effects for all candidate genes or single genes

Description

Since there is more than just one single sgRNA targeting your gene of interest, you can user caRpools to plot different sgRNA phenotype effects, e.g. the fold change or z-ratio, as desribed before in `carpools.raw.genes`. A set of plots can be generated with `carpools.hit.sgrna`, which serves as a wrapper for `carpools.raw.genes`. By default, a foldchange plot as well as a violine plot are generated.

Usage

carpools.hit.sgrna(wilcox=NULL, deseq=NULL, mageck=NULL, dataset=NULL,
dataset.names = NULL, namecolumn=1, fullmatchcolumn=2,
norm.function=median, extractpattern=expression("^(.+?)_.+"),
put.names=TRUE, type="enriched", labelgenes=NULL, cutoff.deseq = 0.05,
cutoff.wilcox = 0.05, cutoff.mageck = 0.05, cutoff.override=FALSE,
plot.genes="overlapping", cutoff.hits=NULL,
plot.type=NULL, controls.target=NULL, controls.nontarget=NULL)

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

dataset

A list of data frames of read-count data as created by load.file(). *Default* none *Values* A list of data frames

namecolumn

In which column are the sgRNA identifiers? *Default* 1 *Values* column number (numeric)

fullmatchcolumn

In which column are the read counts? *Default* 2 *Values* column number (numeric)

dataset.names

A list of names that must be according to the list of data sets given in *dataset*. *Default* NULL *Value* NULL or list of data names (list)

norm.function

The mathematical function to normalize data. By default, the median is used. *Default* median *Values* Any mathematical function of R (function)

extractpattern

PERL regular expression that is used to retrieve the gene identifier from the overall sgRNA identifier. e.g. in **AAK1_107_0** it will extract **AAK1**, since this is the gene identifier beloning to this sgRNA identifier. **Please see: Read-Count Data Files** *Default* expression("^(.+?)(_.+)"), will work for most available libraries. *Values* PERL regular expression with parenthesis indicating the gene identifier (expression)

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"

labelgenes

For which gene shall the sgRNA effects being plotted? This expects a gene identifier or a vector of gene identifiers. If NULL, plots will be generated for all overlapping hit candidate genes. *Default* NULL *Values* A gene identifier or vector of gene identifiers (character)

controls.target

If `type="controls"`, this is the gene identifier of the positive control. *Default* NULL *Value* Gene Identifier (character)

controls.nontarget

If `type="controls"`, this is the gene identifier of the non-targeting control. *Default* "random" *Value* Gene Identifier (character)

put.names

Do you want the sgRNA identifiers to be plotted? *Default* FALSE *Values* TRUE, FALSE

plot.type

WHich kind of plot is to be drawn? If NULL, foldchange and violine plots are generated. *Default* NULL *Values* NULL, "foldchange", "z-score", "z-ratio", "vioplot"

Value

Return generic plots according to `type`.By default, a foldchange plot as well as a violine plot are generated representing log2 fold changes of single sgRNAs.

Details

none

Examples

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)


sgrnas.en = carpools.hit.sgrna(wilcox=data.wilcox, deseq=data.deseq,
    mageck=data.mageck, dataset=list(CONTROL1, CONTROL2, TREAT1, TREAT2),
    dataset.names = c(d.CONTROL1, d.CONTROL2, d.TREAT1, d.TREAT2), namecolumn=1,
    fullmatchcolumn=2, norm.function=median, extractpattern=expression("^(.+?)(_.+)"),
    put.names=TRUE, type="enriched", labelgenes="CASP8", plot.type=NULL, 
    cutoff.deseq = 0.001, cutoff.wilcox=0.05, cutoff.mageck = 0.05,
    cutoff.override=FALSE, cutoff.hits=NULL, controls.target="CASP8", controls.nontarget="random")