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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("iterativeBMA")
In most cases, you don't need to download the package archive at all.
iterativeBMA
The Iterative Bayesian Model Averaging (BMA) algorithm
Bioconductor version: 3.0
The iterative Bayesian Model Averaging (BMA) algorithm is a variable selection and classification algorithm with an application of classifying 2-class microarray samples, as described in Yeung, Bumgarner and Raftery (Bioinformatics 2005, 21: 2394-2402).
Author: Ka Yee Yeung, University of Washington, Seattle, WA, with contributions from Adrian Raftery and Ian Painter
Maintainer: Ka Yee Yeung <kayee at u.washington.edu>
Citation (from within R,
enter citation("iterativeBMA")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("iterativeBMA")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("iterativeBMA")
| R Script | The Iterative Bayesian Model Averaging Algorithm | |
| Reference Manual |
Details
| biocViews | Classification, Microarray, Software |
| Version | 1.24.0 |
| In Bioconductor since | BioC 2.3 (R-2.8) |
| License | GPL (>= 2) |
| Depends | BMA, leaps, Biobase(>= 2.5.5) |
| Imports | |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | http://faculty.washington.edu/kayee/research.html |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | iterativeBMA_1.24.0.tar.gz |
| Windows Binary | iterativeBMA_1.24.0.zip |
| Mac OS X 10.6 (Snow Leopard) | iterativeBMA_1.24.0.tgz |
| Mac OS X 10.9 (Mavericks) | iterativeBMA_1.24.0.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
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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