## Software for local false discovery rate estimation

LFDR-MLE is a suite of R functions for the estimation of local false discovery rates by maximum likelihood under a two-group parametric mixture model of test statistics.

## Shrinkage estimation of expression fold change

Z. Montazeri*, C. M. Yanofsky*, and D. R. Bickel, “Shrinkage estimation of effect sizes as an alternative to hypothesis testing followed by estimation in high-dimensional biology: Applications to differential gene expression,” *Statistical Applications in Genetics and Molecular Biology* **9** (1) 23 (2010). Article | Software

* the first two authors contributed equally

## Significance v. fold change

C. M. Yanofsky and D. R. Bickel, “Validation of differential gene expression algorithms: Application comparing fold change estimation to hypothesis testing,” *BMC Bioinformatics* **11**, 63 (2010). Article

## Gene network reconstruction from transcriptional dynamics

D. R. Bickel, Z. Montazeri, P.-C. Hsieh, M. Beatty, S. J. Lawit, and N. J. Bate, “Gene network reconstruction from transcriptional dynamics under kinetic model uncertainty: A case for the second derivative,” *Bioinformatics* **25**, 772-779 (2009).

## Local false discovery rate software

Zahra Montazeri and David Bickel developed empiricalBayes, an R software bundle that provides a simple solution to the extreme multiple testing problem. It contains two packages:

**localFDR**estimates local false discovery rates given a vector of p-values.**HighProbability**determines which p-values are low enough that their alternative hypotheses can be considered highly probable.