R: Simulate dropout expression data

simulate_dropout {Corbi} | R Documentation

## Simulate dropout expression data

### Description

Generate the expression data with desired dropout rate

### Usage

    simulate_dropout(counts, dropout.rate = 0, dropout.rate.sd = 0.1)

### Arguments

`counts` | expression matrix where each row is a gene and each column is a sample.
`dropout.rate` | the desired average dropout rate of all samples.
`dropout.rate.sd` | the desired standard deviation of dropout rate among 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]