skjt {MBttest} | R Documentation

## Simulated Null Transcriptomic data

### Description

The dataset generated by using R negative binomial pseudorandom generator rnbinom is used as an example for calculating omega.

### Usage

    data("skjt")

### Format

A data frame with 13409 observations on the following 14 variables.

`geneid`

  a string vector

`tagid`

  a numeric vector

`geneid.1`

  a numeric vector

`name`

  a string vector

`chr`

  a string vector

`strand`

  a character vector

`pos`

  a numeric vector

`anno`

  a string vector

`Jurk.NS.A`

  a numeric vector

`Jurk.NS.B`

  a numeric vector

`Jurk.NS.C`

  a numeric vector

`Jurk.48h.A`

  a numeric vector

`Jurk.48h.B`

  a numeric vector

`Jurk.48h.C`

  a numeric vector

### Details

The dataset skjt was generated 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 Jurkat T cell transcriptomic count data . Condition (or treatment) effect on differential transcription of isoforms was set to zero. The data have 13409 genes and 7 information columns: geneid tagid name `chr`,`strand`,`pos`,`anno`, and 6 data columns: `Jurk.NS.A`,`Jurk.NS.B`,`Jurk.NS.C`,`Jurk.48h.A`,`Jurk.48h.B`,`Jurk.48h.C`.

### Value

ID, information, count data of RNA reads

### Source

Simulation.

### 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. DOI: 10.1371/journal.pone.0123658.

### Examples

    data(skjt)
    ## maybe str(skjt) ; plot(skjt) ...

[Package MBttest version 1.14.0 Index]