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 (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.
| Version: |
1.1 |
| Depends: |
R (≥ 2.10), combinat, splines |
| Published: |
2011-09-08 |
| Author: |
Jun Li |
| Maintainer: |
Jun Li <junli07 at stanford.edu> |
| License: |
GPL (≥ 2) |
| CRAN checks: |
PoissonSeq results |
Downloads: