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 (2011). Normalization, testing, and false discovery rate estimation for RNA-sequencing data. To appear, Biostatistics. 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. Software Depends: R(>= 2.10),combinat,splines Jun Li <junli07@stanford.edu> Jun Li GPL (>= 2) 2011-09-08 application/tgz http://CRAN.R-project.org/package=PoissonSeq