oddratio: Calculation of Zeta(zeta)
In MBttest: Multiple Beta t-Tests

Description Usage Arguments Details Value Author(s) References See Also Examples

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).

1	oddratio(XX, na, nb)

`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.

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.

oddrat

list of zeta values

Yuan-De Tan tanyuande@gmail.com

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.

pratio, mbetattest.

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