PoissonSeq: Significance analysis of sequencing data based on a Poisson log linear model

This package implements a method for normalization, testing, and false discovery rate estimation for RNA-sequencing data. The description of the method is in Li J, Witten DM, Johnstone I, Tibshirani R (2012). Normalization, testing, and false discovery rate estimation for RNA-sequencing data. Biostatistics 13(3): 523-38. We estimate the sequencing depths of experiments using a new method based on Poisson goodness-of-fit statistic, calculate a score statistic on the basis of a Poisson log-linear model, and then estimate the false discovery rate using a modified version of permutation plug-in method. A more detailed instruction as well as sample data is available at http://www.stanford.edu/~junli07/research.html. In this version, we changed the way of calculating log foldchange for two-class data. The FDR estimation part remains unchanged.

Version: 1.1.2
Depends: R (≥ 2.10), combinat, splines
Published: 2012-10-10
Author: Jun Li
Maintainer: Jun Li <jun.li at nd.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] (see file LICENSE)
NeedsCompilation: no
CRAN checks: PoissonSeq results


Reference manual: PoissonSeq.pdf
Package source: PoissonSeq_1.1.2.tar.gz
Windows binaries: r-devel: PoissonSeq_1.1.2.zip, r-release: PoissonSeq_1.1.2.zip, r-oldrel: PoissonSeq_1.1.2.zip
OS X Snow Leopard binaries: r-release: PoissonSeq_1.1.2.tgz, r-oldrel: PoissonSeq_1.1.2.tgz
OS X Mavericks binaries: r-release: PoissonSeq_1.1.2.tgz
Old sources: PoissonSeq archive