carpools.read.count.vs: QC: Scatterplots of Read-Counts
In caRpools: CRISPR AnalyzeR for Pooled CRISPR Screens

Description Usage Arguments Details Value Note Author(s) Examples

CaRpools also allows you to compare the readcount for different samples using 'carpools.read.count.vs'. By this, you can easily compare the screen and replicate performance as well as highlighting your non-targeting or positive controls. Moreover, you can highlight any gene as well. For details regarding all arguments and option see '?carpools.read.count.vs'.

carpools.read.count.vs(dataset, namecolumn=1, fullmatchcolumn=2, title="Read Count",
dataset.names = NULL, xlab="Readcount Dataset1", ylab="Readcount Dataset2", xlim=NULL,
ylim=NULL, pch=16, col = rgb(0, 0, 0, alpha = 0.65), labelgenes=NULL, labelcolor="red",
extractpattern=expression("^(.+?)_.+"), plotline=TRUE, normalize=TRUE,
norm.function=median, offsetplot=1.2, center=FALSE, aggregated=FALSE,
pairs=FALSE, type=NULL, plot.identify=FALSE, plot.log=TRUE)

`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)
`title`	The title of the plot. Default "Read Count" Values "Any title" (character)
`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)
`xlab`	Label of X-Axis, only if 'pairs=FALSE' Default "X-Axis" Values "Label of X-Axis" (character)
`ylab`	Label of Y-Axism only if 'pairs=FALSE' Default "Y-Axis" Values "Label of Y-Axis" (character)
`xlim`	You can define the x-axis range being plotted, e.g. 'c(0,1)'. Default empty Values empty or a vector with the lower and upper limit.
`ylim`	You can define the y-axis range being plotted, e.g. 'c(0,1)'. Default empty Values empty or a vector with the lower and upper limit.
`pch`	The type of point used in the plot. See '?par()'. Default 16 Values Any number describing the point, e.g. 16 (numeric)
`col`	The color of the plotted data. Can be any R color or RGB object. See ?rgb() for further information. Default rgb(0, 0, 0, alpha = 0.65) Values Any R color name or RGB color object (character OR color object)
`labelgenes`	You can highlight certain genes within the plot. This expects a gene identifier or a fector of gene identifiers. Default NULL Values A gene identifier or vector of gene identifiers (character)
`labelcolor`	Color to highlight genes stated in 'labelgenes'. Default "organge" Values Any R color or RGB color object.
`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)
`plotline`	You can draw additional lines indicating a fold change of 0, 2, 4. Default TRUE Values* TRUE, FALSE (boolean)
`normalize`	Whether you would like to normalize read-counts first. Recommended if not done already. Default TRUE Values TRUE, FALSE (boolean)
`norm.function`	The mathematical function to normalize data if 'normalize=TRUE'. By default, the median is used. Default median Values Any mathematical function of R (function)
`offsetplot`	Offetplot is used to stretch the x- and y-axis for nicer graphs. This will extend plotting area by offsetplot. Default 1.2 (Plotting area is streched to 1.2 times) Values any number (numeric)
`center`	If you like you can center your data within the plot. Default FALSE Values TRUE, FALSE (boolean)
`aggregated`	If you want to highlight genes, set this to true if you provide already aggregated gene read count instead of sgRNA read counts. Default FALSE Values TRUE, FALSE (boolean)
`pairs`	In the case of plotting all four data sets at once, you can use a pairs plot for easier overview (see '?pairs()'). Default FALSE Values TRUE, FALSE (boolean)
`type`	This indicates whether you would like to color all highlighted genes in either red ("enriched") or blue ("depleted") color according to the standrds in caRpools for plotting enriched or depleted genes after analysis. Default NULL Values NULL, "enriched", "depleted"
`plot.identify`	You can ask R to let you identify genes by clikcing on the dots in the graph. This only works if 'pairs=FALSE'. Default FALSE Values TRUE, FALSE (boolean)
`plot.log`	If all plots are created using log-transformed data. Default TRUE Values TRUE, FALSE (boolean)

For generic plot arguments, see ?plot.

plot.read.count.vs returns a basic plot.

none

Jan Winter

data(caRpools)

carpools.read.count.vs(dataset=list(TREAT1,CONTROL1),
dataset.names = c(d.TREAT1, d.CONTROL1),
  pairs=FALSE, namecolumn=1, fullmatchcolumn=2, title="", pch=16,
  normalize=TRUE, norm.function=median, labelgenes="random", labelcolor="blue",
  center=FALSE, aggregated=FALSE)
  
carpools.read.count.vs(dataset=list(TREAT1, TREAT2, CONTROL1, CONTROL2),
  dataset.names = c(d.TREAT1, d.TREAT2, d.CONTROL1, d.CONTROL2),
  pairs=TRUE, namecolumn=1, fullmatchcolumn=2, title="", pch=16,
  normalize=TRUE, norm.function=median,
  labelgenes="random", labelcolor="blue", center=FALSE, aggregated=FALSE)