To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("sSeq")

In most cases, you don't need to download the package archive at all.

sSeq

   

This package is for version 3.4 of Bioconductor; for the stable, up-to-date release version, see sSeq.

Shrinkage estimation of dispersion in Negative Binomial models for RNA-seq experiments with small sample size

Bioconductor version: 3.4

The purpose of this package is to discover the genes that are differentially expressed between two conditions in RNA-seq experiments. Gene expression is measured in counts of transcripts and modeled with the Negative Binomial (NB) distribution using a shrinkage approach for dispersion estimation. The method of moment (MM) estimates for dispersion are shrunk towards an estimated target, which minimizes the average squared difference between the shrinkage estimates and the initial estimates. The exact per-gene probability under the NB model is calculated, and used to test the hypothesis that the expected expression of a gene in two conditions identically follow a NB distribution.

Author: Danni Yu <dyu at purdue.edu>, Wolfgang Huber <whuber at embl.de> and Olga Vitek <ovitek at purdue.edu>

Maintainer: Danni Yu <dyu at purdue.edu>

Citation (from within R, enter citation("sSeq")):

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("sSeq")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("sSeq")

 

PDF R Script sSeq
PDF   Reference Manual

Details

biocViews RNASeq, Software
Version 1.12.0
In Bioconductor since BioC 2.13 (R-3.0) (3.5 years)
License GPL (>= 3)
Depends R (>= 3.0), caTools, RColorBrewer
Imports
LinkingTo
Suggests
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source sSeq_1.12.0.tar.gz
Windows Binary sSeq_1.12.0.zip
Mac OS X 10.9 (Mavericks) sSeq_1.12.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/sSeq/tree/release-3.4
Package Short Url http://bioconductor.org/packages/sSeq/
Package Downloads Report Download Stats

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