To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("BitSeq")
In most cases, you don't need to download the package archive at all.
BitSeq
Transcript expression inference and differential expression analysis for RNA-seq data
Bioconductor version: 2.14
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: Peter Glaus <glaus at cs.man.ac.uk>
Citation (from within R,
enter citation("BitSeq")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("BitSeq")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("BitSeq")
| R Script | BitSeq User Guide | |
| Reference Manual | ||
| Text | NEWS | |
| Text | LICENSE |
Details
| biocViews | DifferentialExpression, GeneExpression, RNASeq, Sequencing, Software |
| Version | 1.8.0 |
| In Bioconductor since | BioC 2.10 (R-2.15) |
| License | Artistic-2.0 + file LICENSE |
| Depends | Rsamtools, zlibbioc |
| Imports | IRanges |
| Suggests | edgeR, DESeq |
| System Requirements | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | BitSeq_1.8.0.tar.gz |
| Windows Binary | BitSeq_1.8.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | BitSeq_1.8.0.tgz |
| Mac OS X 10.9 (Mavericks) | BitSeq_1.8.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
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