initialize-ASEset: Initialize ASEset

In pappewaio/AllelicImbalance: Investigates Allele Specific Expression

Description

Functions to construct ASEset objects

Usage

ASEsetFromCountList(
  rowRanges,
  countListUnknown = NULL,
  countListPlus = NULL,
  countListMinus = NULL,
  colData = NULL,
  mapBiasExpMean = NULL,
  phase = NULL,
  aquals = NULL,
  verbose = FALSE,
  ...
)

ASEsetFromArrays(
  rowRanges,
  countsUnknown = NULL,
  countsPlus = NULL,
  countsMinus = NULL,
  colData = NULL,
  mapBiasExpMean = NULL,
  phase = NULL,
  genotype = NULL,
  aquals = NULL,
  verbose = FALSE,
  ...
)

Arguments

rowRanges	A GenomicRanges object that contains the variants of interest
countListUnknown	A list where each entry is a matrix with allele counts as columns and sample counts as rows
countListPlus	A list where each entry is a matrix with allele counts as columns and sample counts as rows
countListMinus	A list where each entry is a matrix with allele counts as columns and sample counts as rows
colData	A DataFrame object containing sample specific data
mapBiasExpMean	A 3D array where the SNPs are in the 1st dimension, samples in the 2nd dimension and variants in the 3rd dimension.
phase	A matrix or an array containing phase information.
aquals	A 4-D array containing the countinformation, see details
verbose	Makes function more talkative
...	arguments passed on to SummarizedExperiment constructor
countsUnknown	An array containing the countinformation
countsPlus	An array containing the countinformation
countsMinus	An array containing the countinformation
genotype	matrix

Details

The resulting ASEset object is based on the RangedSummarizedExperiment class, and will therefore inherit the same accessors and ranges operations.

If both countListPlus and countListMinus are given they will be used to calculate countListUnknown, which is the sum of the plus and minus strands.

countListPlus, countListMinus and countListUnknown are i.e. the outputs from the getAlleleCounts function.

aquals is new for the devel branch and will be changed slighly before the relase to include better granularity.

Value

ASEsetFromCountList returns an ASEset object.

Note

ASEsetFromCountList requires the same input data as a RangedSummarizedExperiment, but with minimum one assay for the allele counts.

Author(s)

Jesper R. Gadin, Lasse Folkersen

Examples

#make example alleleCountListPlus
set.seed(42)
countListPlus <- list()
snps <- c('snp1','snp2','snp3','snp4','snp5')
for(snp in snps){
count<-matrix(rep(0,16),ncol=4,dimnames=list(
c('sample1','sample2','sample3','sample4'),
c('A','T','G','C')))
#insert random counts in two of the alleles 
for(allele in sample(c('A','T','G','C'),2)){
count[,allele]<-as.integer(rnorm(4,mean=50,sd=10))
}
countListPlus[[snp]] <- count
}

#make example alleleCountListMinus
countListMinus <- list()
snps <- c('snp1','snp2','snp3','snp4','snp5')
for(snp in snps){
count<-matrix(rep(0,16),ncol=4,dimnames=list(
c('sample1','sample2','sample3','sample4'),
c('A','T','G','C')))
#insert random counts in two of the alleles 
for(allele in sample(c('A','T','G','C'),2)){
count[,allele]<-as.integer(rnorm(4,mean=50,sd=10))
}
countListMinus[[snp]] <- count
}


#make example rowRanges
rowRanges <- GRanges(
seqnames = Rle(c('chr1', 'chr2', 'chr1', 'chr3', 'chr1')),
         ranges = IRanges(1:5, width = 1, names = head(letters,5)),
         snp = paste('snp',1:5,sep='')
         )
#make example colData
colData <- DataFrame(Treatment=c('ChIP', 'Input','Input','ChIP'), 
 row.names=c('ind1','ind2','ind3','ind4'))

#make ASEset 
a <- ASEsetFromCountList(rowRanges, countListPlus=countListPlus, 
countListMinus=countListMinus, colData=colData)

pappewaio/AllelicImbalance documentation built on April 11, 2020, 2:58 a.m.