iChip
Bayesian Modeling of ChIP-chip Data Through Hidden Ising Models
Bioconductor version: 2.9
This package uses hidden Ising models to identify enriched genomic regions in ChIP-chip data. It can be used to analyze the data from multiple platforms (e.g., Affymetrix, Agilent, and NimbleGen), and the data with single to multiple replicates.
Author: Qianxing Mo
Maintainer: Qianxing Mo <moq at mskcc.org>
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("iChip")
To cite this package in a publication, start R and enter:
citation("iChip")
Documentation
| R Script | iChip | |
| Reference Manual |
Details
| biocViews | ChIP-chip, NimbleGen, Microarray, Bioinformatics |
| Depends | R (>= 2.10.0) |
| Imports | limma |
| Suggests | |
| System Requirements | |
| License | GPL (>= 2) |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Version | 1.8.0 |
| Since | Bioconductor 2.6 (R-2.11) |
Package Downloads
| Package Source | iChip_1.8.0.tar.gz |
| Windows Binary | iChip_1.8.0.zip (32- & 64-bit) |
| MacOS 10.5 (Leopard) binary | iChip_1.8.0.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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