View source: R/functions_pool.R
poolPops | R Documentation |
This function combines the information for each individual of each population into information at the population level.
poolPops(nPops, nLoci, indContribution, readsReference)
nPops |
An integer representing the total number of populations in the dataset. |
nLoci |
An integer that represents the total number of independent loci in the dataset. |
indContribution |
Either a list or a matrix (when dealing with a single locus). |
readsReference |
A list, where each entry contains the information for a
single locus. Each list entry should then have one separate entry per
population. Each of these entries should be a matrix, with each row
corresponding to a single individual and each column a different site.
Thus, each entry of the matrix contains the number of observed reads with
the reference allele for that individual at a given site. The output of the
|
In other words, the information of all individuals in a given population is
combined into a single population value and this is done for the various
populations. In this situation, each entry of the indContribution
and
readsReference
lists should contain one entry per population - being, in
essence, a list within a list. Please note that this function is intended to
work for multiple populations and should not be used with a single
population.
a list with three names entries
reference |
a list with one entry per locus. Each entry is a matrix with the number of reference allele reads for each population. Each column represents a different site and each row a different population. |
alternative |
a list with one entry per locus. Each entry is a matrix with the number of alternative 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. |
# 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
poolPops(nPops = 2, nLoci = 1, indContribution = indContribution, readsReference = readsReference)
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