BAC
Bayesian Analysis of Chip-chip experiment
Bioconductor version: 2.10
This package uses a Bayesian hierarchical model to detect enriched regions from ChIP-chip experiments
Author: Raphael Gottardo
Maintainer: Raphael Gottardo <raph at stat.ubc.ca>
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("BAC")
To cite this package in a publication, start R and enter:
citation("BAC")
Documentation
| R Script | 1. Primer | |
| Reference Manual |
Details
| biocViews | Microarray,Transcription,Bioinformatics, Software |
| Depends | R (>= 2.10) |
| Imports | |
| Suggests | |
| System Requirements | |
| License | Artistic-2.0 |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Version | 1.16.0 |
| Since | Bioconductor 2.2 (R-2.7) |
Package Downloads
| Package Source | BAC_1.16.0.tar.gz |
| Windows Binary | BAC_1.16.0.zip (32- & 64-bit) |
| MacOS 10.5 (Leopard) binary | BAC_1.16.0.tgz |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Annotation
- Variants
- Flow Cytometry and other assays
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