fitNL: Fit Negative Binomial Mixture Model

In SIBERG: Systematic Identification of Bimodally Expressed Genes Using RNAseq Data

Fit Negative Binomial Mixture Model

Description

The function fits a two-component Negative Binomial mixture model.

Usage

fitNL(y, d=NULL, model='E')

Arguments

y	A vector representing the transformed data that follows the normal mixture distribution.
d	A vector of the same length as y representing the normalization constant to be applied to the data.
model	Character specifying E or V model. E model fits the mixture model with equal variance while V model doesn't put any constraint.

Details

This function calls the mclust package to fit the 2-component normal mixture.

Value

A vector consisting parameter estimates of mu1, mu2, phi1, phi2, pi1, logLik and BIC.

Author(s)

Pan Tong ([e-mail]), Kevin R Coombes ([e-mail])

References

Wang, J.,Wen, S., Symmans,W., Pusztai, L., and Coombes, K. (2009). The bimodality index: a criterion for discovering and ranking bimodal signatures from cancer gene expression profiling data. Cancer informatics, 7, 199.

Fraley, C. and Raftery, A. (2002). Model-based clustering, discriminant analysis, and density estimation. Journal of the american statistical association, 97(458), 611:631.

Tong, P., Chen, Y., Su, X. and Coombes, K. R. (2012). Systematic Identification of Bimodally Expressed Genes Using RNAseq Data. Bioinformatics, 2013 Mar 1;29(5):605-13.

See Also

SIBER fitLN fitNB fitGP

Examples

# artificial microarray data from normal distribution
set.seed(1000)
dat <- rnorm(100, mean=5, sd=1)
fitNL(y=dat)

SIBERG documentation built on May 3, 2022, 9:07 a.m.