To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("BitSeq")
In most cases, you don't need to download the package archive at all.
Bioconductor version: 3.2
The BitSeq package is targeted for transcript expression analysis and differential expression analysis of RNA-seq data in two stage process. In the first stage it uses Bayesian inference methodology to infer expression of individual transcripts from individual RNA-seq experiments. The second stage of BitSeq embraces the differential expression analysis of transcript expression. Providing expression estimates from replicates of multiple conditions, Log-Normal model of the estimates is used for inferring the condition mean transcript expression and ranking the transcripts based on the likelihood of differential expression.
Author: Peter Glaus, Antti Honkela and Magnus Rattray
Maintainer: Antti Honkela <antti.honkela at hiit.fi>, Panagiotis Papastamoulis <panagiotis.papastamoulis at manchester.ac.uk>
Citation (from within R,
enter citation("BitSeq")
):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("BitSeq")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("BitSeq")
BitSeq User Guide | ||
Reference Manual | ||
Text | NEWS | |
Text | LICENSE |
biocViews | AlternativeSplicing, Bayesian, DifferentialExpression, DifferentialSplicing, GeneExpression, RNASeq, Sequencing, Software, Transcription |
Version | 1.14.0 |
In Bioconductor since | BioC 2.10 (R-2.15) (4 years) |
License | Artistic-2.0 + file LICENSE |
Depends | Rsamtools, zlibbioc |
Imports | S4Vectors, IRanges |
LinkingTo | Rsamtools(>= 1.19.38), zlibbioc |
Suggests | edgeR, DESeq, BiocStyle |
SystemRequirements | |
Enhances | |
URL | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Package Source | BitSeq_1.14.0.tar.gz |
Windows Binary | BitSeq_1.14.0.zip (32- & 64-bit) |
Mac OS X 10.6 (Snow Leopard) | BitSeq_1.14.0.tgz |
Mac OS X 10.9 (Mavericks) | BitSeq_1.14.0.tgz |
Subversion source | (username/password: readonly) |
Git source | https://github.com/Bioconductor-mirror/BitSeq/tree/release-3.2 |
Package Short Url | http://bioconductor.org/packages/BitSeq/ |
Package Downloads Report | Download Stats |
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