betattest {MBttest} | R Documentation

## Beta t-test

### Description

Beta t-test and degree of freedom for each gene or isoform are calculated in this function.

### Usage

    betattest(X, na, nb)

### Arguments

`X` | count data of RNA reads containing N genes (or isoforms).
`na` | number of replicate libraries in condition A
`nb` | number of replicate libraries in condition B

### Details

In beta t-test,

t=\frac{(P_A-P_B)}{√(V_A+V_B)}

where P_A and P_B are proportions of a gene or an isoform in conditions A and B, V_A and V_B are variances estimated in conditions A and B. They are outputted by betaparametVP.

### Value

return two lists:

`t` | t-value list.
`df` | df list. df is degree of freedom.

### Note

If pooled standard error is zero, then the t-value is not defined and set to be zero.

### Author(s)

Yuan-De Tan tanyuande@gmail.com

### References

Baggerly KA, Deng L, Morris JS, Aldaz CM (2003) Differential expression in SAGE: accounting for normal between-library variation. Bioinformatics, 19: 1477-1483.
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. 2015 DOI: 10.1371/journal.pone.0123658.

### See Also

`pratio`, `oddratio`.

### Examples

    data(jkttcell)
    X<-jkttcell[1:1000,]
    na<-3
    nb<-3
    cn<-ncol(X)
    rn<-nrow(X)
    XC<-X[,1:(cn-na-nb)]
    XX<-X[,(cn-na-nb+1):cn]
    betattest<-betattest(XX,na=3,nb=3)

[Package MBttest version 1.14.0 Index]