simCountMat: Simulate a count matrix

In hallucigenia-sparsa/seqtime: Time Series Analysis of Sequencing Data

Simulate a count matrix

Description

Simulate the output of a sequencing experiment, with taxa as rows and samples as columns.

Usage

simCountMat(N, pi = c(), samples = 100, counts = 1000,
  distrib = "dm", maxcount = 100, mode = 1, k = 0.5,
  theta = 0.002, norm = F, shuffle.samples = F)

Arguments

N	the number of taxa
pi	taxon proportion vector of length N (if smaller N, it is generated using the mode and k parameters)
samples	the number of columns in the matrix
counts	either the total number of counts in each sample or a vector specifying the count number in each sample
distrib	"dm" for Dirichlet-Multinomial distribution or "unif" for uniform distribution
maxcount	maximal count number for any taxon (only for uniform distribution)
mode	how the taxon probability vector for the DM distribution is to be generated (1=perfectly even, 2=sampled from uniform distribution, 3=dominant taxon has probability of 0.95 and all others have equal probability, 4=probabilities are sampled from a Poisson distribution with lambda set to 0.5, 5=using bstick function from vegan, 6=using geometric series with parameter k)
k	evenness parameter of mode 6
theta	overdispersion parameter of the DM distribution
norm	normalize matrix column-wise, such that the entries in each column add to one
shuffle.samples	shuffle each sample

Value

a count matrix or relative abundance matrix

See Also

generateAbundances

Examples

tsplot(simCountMat(N=10,samples=50,mode=6,k=0.5),header="Dirichlet-Multinomial")

hallucigenia-sparsa/seqtime documentation built on Jan. 9, 2023, 11:53 p.m.