pool2sync {poolHelper}

Create 'synchronized' file from Pool-seq data

Description

Creates and saves a file with the information from Pool-seq data coded in the 'synchronized' format.

Usage

pool2sync(reference, alternative, file, pos = NULL)

Arguments

reference

is a list where each entry corresponds to a different locus. Each list entry is a vector with the number of reads with the reference allele. Each entry of the vector corresponds to a different SNP. This list can have a single entry if the data is comprised of a single locus.

alternative

is a list where each entry corresponds to a different locus. Each list entry is a vector with the number of reads with the alternative allele. Each entry of the vector corresponds to a different SNP. This list can have a single entry if the data is comprised of a single locus.

file

is a character string naming the file to write to.

pos

is an optional input (default is NULL). If the actual position of the SNPs are known, they can be used as input here. When working with a single locus, this should be a numeric vector with each entry corresponding to the position of each SNP. If the data has multiple loci, this should be a list where each entry is a numeric vector with the position of the SNPs for a different locus.

Details

It starts by converting the number of reads with the reference allele and the alternative allele to a A-count:T-count:C-count:G-count:N-count:deletion-count string. Here, we assume that the reference allele is always A and the alternative is always T.

Then, this A-count:T-count:C-count:G-count:N-count:deletion-count string is combined with other necessary information such as the chromosome of each SNP, the position of the SNP and the reference character. This step creates a data frame where each row corresponds to a different SNP.

A file is then created and saved in the current working directory, with the Pool-seq data coded in the 'synchronized' file format.

Value

a file in the current working directory containing Pool-seq data in the 'synchronized' format.

Examples

# simulate Pool-seq data for 100 individuals sampled at a single locus
genotypes <- run_scrm(nDip = 100, nloci = 1, theta = 5)
# simulate Pool-seq data assuming a coverage of 100x and two pools of 50 individuals each
pool <- simPoolseq(genotypes = genotypes, pools = c(50, 50), pError = 100, sError = 0.001,
mCov = 100, vCov = 250, min.minor = 0)
# create a 'synchronized' file of the simulated data - this will create a txt file
# pool2sync(reference = pool$reference, alternative = pool$alternative, file = "mysync.txt")

# simulate Pool-seq data for 10 individuals sampled at 5 loci
genotypes <- run_scrm(nDip = 10, nloci = 5, theta = 5)
# simulate Pool-seq data assuming a coverage of 100x and a single pool of 10 individuals
pool <- simPoolseq(genotypes = genotypes, pools = 10, pError = 100, sError = 0.001,
mCov = 100, vCov = 250, min.minor = 0)

# create a 'synchronized' file of the simulated data - this will create a txt file
# pool2sync(reference = pool$reference, alternative = pool$alternative, file = "mysync.txt")