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.

Author
Jun Li
Date of publication
2012-10-10 15:36:34
Maintainer
Jun Li <jun.li@nd.edu>
License
GPL (>= 2)
Version
1.1.2

View on CRAN

Man pages

dat
A toy RNA-Seq data.
PS.Est.Depth
estimate the sequencing depths
PS.Main
detecting differentially expressed genes from RNA-Seq data.

Files in this package

PoissonSeq
PoissonSeq/MD5
PoissonSeq/man
PoissonSeq/man/dat.Rd
PoissonSeq/man/PS.Est.Depth.Rd
PoissonSeq/man/PS.Main.Rd
PoissonSeq/data
PoissonSeq/data/dat.RData
PoissonSeq/NAMESPACE
PoissonSeq/DESCRIPTION
PoissonSeq/LICENSE
PoissonSeq/R
PoissonSeq/R/ps_main.R
PoissonSeq/R/ps_cmeans.R
PoissonSeq/R/ps_order.R
PoissonSeq/R/ps_other.R
PoissonSeq/R/ps_stat.R
PoissonSeq/R/ps_rand.R
PoissonSeq/R/ps_fdr.R