findMinor {poolHelper}

Define major and minor alleles

Description

This function checks which of the two simulated alleles (reference or alternative) corresponds to the minor allele. This function can also be used to remove sites according to a minor-allele reads threshold.

Usage

findMinor(reference, alternative, coverage)

Arguments

reference

is a matrix of reference allele reads. Each row of the matrix should be a different population and each column a different site. Thus, each entry of the matrix contains the number of observed reads with the reference allele for that population at a given site.

alternative

is a matrix of alternative allele reads. Each row of the matrix should be a different population and each column a different site. Thus, each entry of the matrix contains the number of observed reads with the alternative allele for that population at a given site.

coverage

is a matrix of total coverage. Each row of the matrix should be a different population and each column a different site. Thus, each entry of the matrix contains the total number of observed reads for that population at a given site.

Details

More precisely, this function counts the number of reads with the reference or alternative allele at each site and then sets the minor allele as the least frequent of the two. This is done across all populations and so the major and minor alleles are defined at a global level. Then if the min.minor input is not NA, sites where the number of minor allele reads, across all populations, is below the user-defined threshold are removed.

Value

a list with three names entries

major

a list with one entry per locus. Each entry is a matrix with the number of major allele reads for each population. Each column represents a different site and each row a different population.

minor

a list with one entry per locus. Each entry is a matrix with the number of minor allele reads for each population. Each column represents a different site and each row a different population.

total

a list with one entry per locus. Each entry is a matrix with the coverage of each population. Each column represents a different site and each row a different population.

Examples

# simulate coverage at 5 SNPs for two populations, assuming 20x mean coverage
reads <- simulateCoverage(mean = c(20, 20), variance = c(100, 100), nSNPs = 5, nLoci = 1)

# simulate the number of reads contributed by each individual
# for each population there are two pools, each with 5 individuals
indContribution <- popsReads(list_np = rep(list(rep(5, 2)), 2), coverage = reads, pError = 5)

# set seed and create a random matrix of genotypes for the 20 individuals - 10 per population
set.seed(10)
genotypes <- matrix(rpois(100, 0.5), nrow = 20)

# simulate the number of reference reads for the two populations
readsReference <- numberReferencePop(genotypes = genotypes, indContribution = indContribution,
size = rep(list(rep(5, 2)), 2), error = 0.01)

# create Pooled DNA sequencing data for these two populations and for a single locus
pools <- poolPops(nPops = 2, nLoci = 1, indContribution = indContribution,
readsReference = readsReference)

# define the major and minor alleles for this Pool-seq data
# we have to select the first entry of the pools list because this function works for matrices
findMinor(reference = pools$reference[[1]], alternative = pools$alternative[[1]],
coverage = pools$total[[1]])