A gene expression matrix of counts with N features and length(n) pairs of samples. The first pair corresponds to the two first column and so on. The total number of samples is 2*n The distribution of the first component is Poisson with parameter lambda1. For the genes (rows) in gs the distribution is the sum of the first generated value plus a random count with Poisson distribution with mean lambda2. For the genes (rows) not in gs the distribution of the second component is the sum of the first generated value plus a random count with Poisson distribution with mean lambda3. The matrix outlier contains in the first column the indices of rows and in the second column the indices of pairs. For the pairs of counts in outlier the first component follows a Poisson distribution with mean lambda1 and the second component is equal to the first one plus a random count with Poisson distributed with mean lambda4.

rPairedPoisson(n, N, lambda1, lambda2, lambda3, lambda4, gs = NULL,
  outlier = NULL)

Arguments

n

Number of pairs

N

Number of genes

lambda1

Mean of the first component

lambda2

Mean of the random count added to the first generated value on the significant genes

lambda3

Mean of the random count added to the first generated value on the non significant genes

lambda4

Mean of the random count added to the first generated value on the outlier genes given in outlier

gs

Significant gene set (a subset of rows in 1:N)

outlier

Matrix (rows as genes and pairs as samples) where the corresponding pair of counts are an outlier gs == NULL correspond with no differential expression