To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("baySeq")
In most cases, you don't need to download the package archive at all.
baySeq
Empirical Bayesian analysis of patterns of differential expression in count data
Bioconductor version: 2.14
This package identifies differential expression in high-throughput 'count' data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods.
Author: Thomas J. Hardcastle
Maintainer: Thomas J. Hardcastle <tjh48 at cam.ac.uk>
Citation (from within R,
enter citation("baySeq")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("baySeq")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("baySeq")
| R Script | baySeq | |
| Reference Manual |
Details
| biocViews | Bioinformatics, DifferentialExpression, HighThroughputSequencing, MultipleComparisons, SAGE, Software |
| Version | 1.18.0 |
| In Bioconductor since | BioC 2.5 (R-2.10) |
| License | GPL-3 |
| Depends | R (>= 2.3.0), methods, GenomicRanges |
| Imports | |
| Suggests | snow, edgeR |
| System Requirements | |
| URL | |
| Depends On Me | EDDA, Rcade, segmentSeq, TCC |
| Imports Me | EDDA, metaseqR, segmentSeq |
| Suggests Me | compcodeR, oneChannelGUI |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | baySeq_1.18.0.tar.gz |
| Windows Binary | baySeq_1.18.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | baySeq_1.18.0.tgz |
| Mac OS X 10.9 (Mavericks) | baySeq_1.18.0.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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