omega: Omega calcularion
In tatest: Two-Group Ta-Test

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

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.

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

`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".

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

return a numeric value

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.

momega, rhov

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