simulate_dropout2 {Corbi}R Documentation

Simulate dropout expression data

Description

Generate the expression data with desired dropout rate range

Usage

simulate_dropout2(counts, min.rate = 0, max.rate = 0.8)

Arguments

counts

expression matrix where each row is a gene and each column is a sample.

min.rate

the minimum dropout rate of all samples.

max.rate

the maximum dropout rate of all samples.

Details

The dropout event is modelled by a logistic distribution such that the low expression genes have higher probability of dropout. The expression value of genes in a sample are randomly set to zero with probabilities associated with their true expression values until the desired dropout rate for that sample is meet.

Value

This function will return a list with the following components:

counts

The modified expression matrix with the same dimension as input counts.

original.counts

The original input expression matrix.

dropout

The binary matrix indicating where the dropout events happen.

References

Peter V. Kharchenko, Lev Silberstein, and David T. Scadden. Bayesian approach to single-cell differential expression analysis. Nature Methods, 11(7):740–742, 2014.


[Package Corbi version 0.6-1 Index]