poolHelper (version 1.1.0)

maePool: Average absolute difference between allele frequencies

Description

Calculates the average absolute difference between the allele frequencies computed directly from genotypes and from pooled sequencing data.

Usage

maePool(
  nDip,
  nloci,
  pools,
  pError,
  sError,
  mCov,
  vCov,
  min.minor,
  minimum = NA,
  maximum = NA,
  theta = 10
)

Value

a data.frame with columns detailing the number of diploid individuals, the pool error, the number of pools, the number of individuals per pool, the mean coverage, the variance of the coverage and the average absolute difference between the frequencies computed from genotypes and from pooled data.

Arguments

nDip

an integer representing the total number of diploid individuals to simulate. Note that scrm::scrm() actually simulates haplotypes, so the number of simulated haplotypes is double of this.

nloci

is an integer that represents how many independent loci should be simulated.

pools

a list with a vector containing the size (in number of diploid individuals) of each pool. Thus, if a population was sequenced using a single pool, the vector should contain only one entry. If a population was sequenced using two pools, each with 10 individuals, this vector should contain two entries and both will be 10.

pError

an integer representing the value of the error associated with DNA pooling. This value is related with the unequal contribution of both individuals and pools towards the total number of reads observed for a given population - the higher the value the more unequal are the individual and pool contributions.

sError

a numeric value with error rate associated with the sequencing and mapping process. This error rate is assumed to be symmetric: error(reference -> alternative) = error(alternative -> reference). This number should be between 0 and 1.

mCov

an integer that defines the mean depth of coverage to simulate. Please note that this represents the mean coverage across all sites.

vCov

an integer that defines the variance of the depth of coverage across all sites.

min.minor

is an integer representing the minimum allowed number of minor-allele reads. Sites that, across all populations, have less minor-allele reads than this threshold will be removed from the data.

minimum

an optional integer representing the minimum coverage allowed. Sites where the population has a depth of coverage below this threshold are removed from the data.

maximum

an optional integer representing the maximum coverage allowed. Sites where the population has a depth of coverage above this threshold are removed from the data.

theta

a value for the mutation rate assuming theta = 4Nu, where u is the neutral mutation rate per locus.

Details

Different combinations of parameters can be tested to check the effect of the various parameters. The average absolute difference is computed with the mae function, assuming the frequencies computed directly from the genotypes as the actual input argument and the frequencies from pooled data as the predicted input argument.

Examples

# single population sequenced with a single pool of 100 individuals
maePool(nDip = 100, nloci = 10, pools = list(100), pError = 100, sError = 0.01,
mCov = 100, vCov = 250, min.minor = 2)

# single population sequenced with two pools, each with 50 individuals
maePool(nDip = 100, nloci = 10, pools = list(c(50, 50)), pError = 100, sError = 0.01,
mCov = 100, vCov = 250, min.minor = 2)

# single population sequenced with two pools, each with 50 individuals
# removing sites with coverage below 10x or above 180x
maePool(nDip = 100, nloci = 10, pools = list(c(50, 50)), pError = 100, sError = 0.01,
mCov = 100, vCov = 250, min.minor = 2, minimum = 10, maximum = 180)