oddratio {MBttest} | R Documentation

## Calculation of Zeta(ζ)

### Description

Zeta (ζ) is used to measure homogeneity intensity of two subdatasets. If ζ >1, these two subdatasets have good homogeneity; otherwise, ζ <1 indicates that two subdatasets have poor homogeneity (big noise).

### Usage

    oddratio(XX, na, nb)

### Arguments

`XX` | count data of RNA reads generated by next generation sequencing.
`na` | number of replicate libraries in condition A.
`nb` | number of replicate libraries in condition B.

### Details

Zeta is defined as

ζ=log(1+\frac{\bar{X}σ^2+1}{\bar{X}_Aσ^2_A+\bar{X}_Bσ^2_B+1})

where ζ is different from ψ. If two subdatasets have big a gap and good homogeneity, then ζ value has much larger than 1.

### Value

`oddrat` | list of zeta values

### 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. 2015 DOI: 10.1371/journal.pone.0123658.

### See Also

`pratio`, `mbetattest`.

### Examples

    XX<-matrix(NA,2,8)
    XX[1,]<-c(112,122, 108,127,302, 314, 322, 328)
    XX[2,]<-c(511, 230, 754, 335,771, 842, 1014,798)
    #XX
    #     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
    #[1,]  112  122  108  127  302  314  322  328
    #[2,]  511  230  754  335  771  842 1014  798
    oddratio(XX=XX,na=4,nb=4)

    #[1] 3.9432676 0.8762017

    # see example in mbetattest

[Package MBttest version 1.14.0 Index]