maskBAD (version 1.16.0)

mask: Filtering/Masking expression data

Description

Identyfying probes with binding affinity difference (BAD probes) between two groups of samples on the basis of expression data.

Usage

mask(affy,exprlist=NULL,useExpr=TRUE,ind,PM=FALSE,verbose=TRUE)

Arguments

affy

An object of class AffyBatch.

exprlist

A vector with probesetnames to be used. If NULL, all probesets are analyzed.

useExpr

Logical. If 'TRUE', only expressed genes (see Details) are used. If 'FALSE', all probes are analyzed.

ind

Numeric vector, with values 1 and 2, definining group assignement for samples in affy.

PM

Logical. If 'TRUE', only probes with a mean pm value greater than the mean mm value are used.

verbose

Logical. If 'TRUE', it writes out some messages indicating progress. If 'FALSE' nothing should be printed.

Value

A list of two objects will be returned.

probes

A data frame with x,y coordinates, quality score and probeset for each analyzed probe.

notUsed

If PM=TRUE: A vector with unused probes having a lower pm mean value than mm mean value.

Details

The function mask identifies in expression data probes which binding affinity (BAD probes) differs between two groups of samples, e.g two species. The basic input data is AffyBatch object(expresssion data prepared using the function ReadAffy from the library Affy) and a vector defining group assignement of samples. As masking is based on expression values, only expressed probes should be used. As a default they are defined by the affy function mas5calls and condition of being expressed (having "P" value) in at least 90% of samples from each group, but any set of probesets might be submitted with exprlist argument. Probes are analyzed for difference in binding affinity between groups. Each probe is assigned a quality score, based on all pairwise probes' correlations within probesets (for details see vignette or paper). Probes' quality scores, their x and y coordinates on the microarray and the probeset names are stored in a matrix.

References

Dannemann et al, The effects of probe binding affinity differences on gene expression measurements and how to deal with them. Bioinformatics 2009 \ Khaitovich et al,Parallel Patterns of Evolution in the Genomes and Transcriptomes of Humans and Chimpanzees, Science 2005

See Also

overlapExprExtMasks, prepareMaskedAffybatch, mas5calls, plotProbe

Examples

data(AffyBatch)
## we provide 20 samples (10 for both human and chimpanzee)
## the first 10 entries are chimpanzee samples the last 10 from human
ind.vec=rep(1:2,each=10)
## mask on AffyBatch with all genes 
exmask <-
mask(newAffyBatch,ind=ind.vec,PM=TRUE,useExpr=FALSE)