skjt: Simulated Null Transcriptomic data

In Yuande/MBttest: Multiple Beta t-Tests

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) ...

Yuande/MBttest documentation built on Aug. 25, 2022, 12:58 a.m.