Reduced matrix of CNV blocks across the whole genome

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Description

Obtains the reduced matrix of CNV segments and subject samples from segmentation output. The initail matrix is obtained and reduced for each cromosome in turn. The resulting matrix is a concatenation of the reduced matrices for each chromosome.

Usage

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getReducedData(x, gg, varSimil = 0.99, subVariation = 0.99)

Arguments

x

concatenated list containing segmentation outcome for each subject, chromosome and population.

gg

genetic info: data.frame with probe names, chromosome number and genomic positions of each CNV.

varSimil

varSimil=0.99 produces blocks of neighboring CNVs which do differ in more than 99% across the subject sample.

subVariation

subVariation = 0.99 gets rid of CNV blocks that are constant across the the whole subject sample, except for 1% of the subjects.

Details

For x, concatenation by subject and chromosome, within a single population, is readily provided by the function summary.parGADA on an object parGADA that has been previously segemnted. Population concatenation is the result of c(summary{parGADA1}), summary{parGADA2}), ... across groups. Concatenation can be obtained with the function sortPopData(segments,nchr,npop), where segments is the output of GADA, nchr the number of chromosomes analyzed and npop the number of populations in the data set.

Value

getReducedData

produces a data.frame with colums as.factors representing each CNV block

attr(getReducedData,"cnv.blocks"

lists the genetic information of each CNV block

Author(s)

Alejandro Caceres

See Also

reduceMatrix, getChromosomeDat

Examples

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## Not run: 

# 'Hapmap270Cnv.RData' file can be downloaded from ...

load("Hapmap270Cnv.RData")

mat.f<-getReducedData(segments, gen.info, varSimil=0.99, subVariation=0.90)
cnv.blocks<-attr(mat.f,"cnv.blocks")
matrixPlot(mat.f)

#if segments are available form gada output first sort data by populations then get reduced data.
#segments<-sortPopData(segments,nchr,npop)
#mat.f<-getReducedData(segments, gen.info, varSimil=0.99, subVariation=0.90)


## End(Not run)