BatchCorrection: Batch correct data sets using a pre-calculated set of...

In DepMap-Analytics/IntCRISPR: Integrates two separate genome-wide CRISPR screens

Description

Calculates the correction vectors based on the ComBat function from the R sva package for removing batch effects. Two datasets of the same models (e.g. screens of cell lines) from two different batches are input and the batch correction vectors returned. Can be used to calculate batch effects from a subset of screens e.g. those cell lines screened in all batches. The correction vectors output from this function can then be applied to non-overlapping screens.

Usage

BatchCorrection(data1,data2,site1="Broad",site2="Sanger",CombatRes,stdPrior=TRUE,qcThresh=NULL,qcvalues1=NULL,qcvalues2=NULL)

Arguments

data1	Matrix of first data set to be batch corrected. Rows should be genes columns screens. Recommended data is quantile normalised before passing to this function.
data2	Matrix of second data set to be batch corrected. Rows should be genes columns screens. Recommended data is quantile normalised before passing to this function.
site1	Default Broad. Character abel for batch of data1
site2	Default Sanger. Character label for batch of data1
CombatRes	Output for the ComBatCP function.
stdPrior	Default TRUE. Should genes be standardised first using mean and variance values from the ComBatRes output.
qcThresh	Optional, default NULL. Minimum quality score to include screen in correction and final dataset
qcvalues1	Default NULL. QC values required when qcThresh is used. The vector should relate to the columns of data1 giving quality scores for each screen.
qcvalues2	Default NULL. QC values required when qcThresh is used. The vector should relate to the columns of data2 giving quality scores for each screen.

Examples

#Not run

#OrigAll<-BatchCorrection(data1=BroadData,data2=SangerData,CombatRes=CombatOrig)

DepMap-Analytics/IntCRISPR documentation built on Feb. 1, 2021, 4:05 p.m.