simulat {MBttest} | R Documentation

## Simulation Data

### Description

This function uses negative binomial (NB) pseudorandom generator to create any count datasets of RNA isoform reads based on real data.

### Usage

    simulat(yy, nci, r1, r2, p, q, A)

### Arguments

`yy` | real count data
`nci` | numeric argument: column number of information related to genes or isoforms.
`r1` | numeric argument: number of replicate libraries in condition 1.
`r2` | numeric argument: number of replicate libraries in condition 2.
`p` | numeric argument: proportion of genes or isoforms differentially expressed. The value is in range of 0 ~1. Default value is 0.
`q` | numeric argument: proportion of genes or isoforms artificially noised. The value is in range of 0 ~1. Default value is 0.
`A` | numeric argument: conditional effect value. The value is larger than or equal to 0. Default value is 0.

### Details

Null count data are created by using R negative binomial pseudorandom generator rnbinom with mu and size. Parameters mu and size are given by mean and variance drawn from real read counts of a gene or an isoforms in a condition. Condition (or treatment) effect on differential transcription of isoforms is linearly and randomly assigned to genes or isoforms. The conditional effect = AU where U is uniform variable and A is an input constant. P percent of genes or isoforms are set to be differentially expressed or differentially spliced. Q percent of genes or isoforms have technical noise. If P = 0, then simulation is null simulation, the data are null data or baseline data.

### Value

Return count data.

### Author(s)

Yuan-De Tan tanyuande@gmail.com

### References

Yuan-De Tan Anita M. Chandler, Arindam Chaudhury, and Joel R. Neilson(2015) A Powerful Statistical Approach for Large-scale Differential Transcription Analysis.Plos One, 10.1371/journal.pone.0123658.

### See Also

`NegBinomial`

### Examples

    data(jkttcell)
    jknull<-simulat(yy=jkttcell[1:500,],nci=7,r1=3,r2=3,p=0,q=0.2,A=0)

[Package MBttest version 1.20.0 Index]