simulateMOI: Simple simulation of MOI SNV data

In bahlolab/moimix: Estimating mulitplicity of infection from high-throughput sequencing data

Description

Generate read count data in support of SNVs partioned by mixtures of clones within a host. This is done by setting true clonal mixture proportions and the underlying sampling probabilities for each clone. Then a random sample of underlying SNV probabilities is sampled from either a rbeta or rtexp distrubition with given parameters and read counts are generated by bionimial conditonal on the underlying SNV probability with the clone sampling probabilities.

Usage

simulateMOI(
  n.samples,
  n.snps,
  moi,
  mean_coverage,
  error_coverage,
  pi.true = NULL,
  mu.true = NULL
)

Arguments

n.samples	number of infected hosts in population
n.snps	number of SNPs observed
moi	number of clonal infections
mean_coverage	average coverage of reads
error_coverage	deviation in coverage of reads
pi.true	optional matrix of true mixture proportions
mu.true	optional matrix of true mixture components

Value

A list containing the following elements pi.true an n.samples by moi matrix containing true clonal proportions mu.true an n.samplps by moi matrix containing true genotype proportions aaf an n.snps vector of under SNV probabilities read.counts an n.samples by n.snps matrix containing read counts supporting each SNV error.counts an n.samples by n.snps matrix containing number of error reads

bahlolab/moimix documentation built on April 16, 2020, 8:40 a.m.