NBBttest (version 1.0.1)

oddratio: Calculation of zeta (\(\zeta\))

Description

\(\zeta\) is used to measure homogeneity intensity of two subdatasets. If \(\zeta\) is larger than 1, these two subdatasets have good homogeneity; otherwise, \(\zeta <1\) indicates that two subdatasets have poor homogeneity (big noise).

Usage

oddratio(XX, na, nb)

Arguments

XX

nonnegative 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.

Value

zeta vector.

Details

Zeta (\(\zeta\)) is defined as $$\zeta=ln\left(1+\frac{\bar{X} \times \sigma^2 +1}{\bar{X}_A\times \sigma^2_A+\bar{X}_B\times \sigma^2_B+1}\right) $$ where \(\zeta\) is different from \(\psi\). If two subdatasets have big a gap and good homogeneity,then seta value has much larger than 1.

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

# NOT RUN {
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)
oddratio(XX=XX,na=4,nb=4)
# }