betattest: Beta t-test

In Yuande/MBttest: Multiple Beta t-Tests

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 [e-mail]

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)

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