omega: Omega calcularion

In tatest: Two-Group Ta-Test

Description

Omega (ω) function is a function that is used to estimate omega using simulate null data from negative bionomial distribution. Omege is a null rho that is used as a threshold for real rho. Simulation is dependent on the original data.

Usage

omega(XA, XB, na, nb, m, alpha = 0.05, distr = "norm")

Arguments

XA	a numeric vector values of condition A
XB	a numeric vector values of condition b
na	a numeric value, sample size in A.
nb	a numeric value, sample size in B
m	simulation number specified.
alpha	a numeric value, statistical cutoff. Default is 0.05.
distr	data distribution specified for data. For current version, we consider three distributions: normal, negative binomial (NB) and uniform. Default distribution is "norm". If user believe that the data follow negative binomial distribution, then set distr="NB" or "negative binomial" or if the data follow uniform distribution, then set distr="unif"or "uniform".

Details

This function is to use simulated null data to calculate omega value with rho = 1.

Value

return a numeric value

Author(s)

Yuan-De Tan [e-mail]

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

momega, rhov

Examples

X<-c(112,122,108,127)
Y<-c(302, 314,322,328)
omega(XA=X, XB=Y, na=4, nb=4, m=2000, alpha = 0.05)
#[1] 0.9055152
 omega(XA=X, XB=Y, na=4, nb=4, m=2000, alpha = 0.05,distr="NB")
#[1] 0.8995424
omega(XA=X, XB=Y, na=4, nb=4, m=2000, alpha = 0.05,distr="uniform")
#[1] 0.97194

tatest documentation built on May 2, 2019, 6:01 a.m.