To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("CMA")
In most cases, you don't need to download the package archive at all.
CMA
Synthesis of microarray-based classification
Bioconductor version: 2.14
This package provides a comprehensive collection of various microarray-based classification algorithms both from Machine Learning and Statistics. Variable Selection, Hyperparameter tuning, Evaluation and Comparison can be performed combined or stepwise in a user-friendly environment.
Author: Martin Slawski <ms at cs.uni-sb.de>, Anne-Laure Boulesteix <boulesteix at ibe.med.uni-muenchen.de>, Christoph Bernau <bernau at ibe.med.uni-muenchen.de>.
Maintainer: Christoph Bernau <bernau at ibe.med.uni-muenchen.de>
Citation (from within R,
enter citation("CMA")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("CMA")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("CMA")
| R Script | CMA_vignette.pdf | |
| Reference Manual |
Details
| biocViews | Classification, Software |
| Version | 1.22.0 |
| In Bioconductor since | BioC 2.3 (R-2.8) |
| License | GPL (>= 2) |
| Depends | R (>= 2.10), methods, stats, Biobase |
| Imports | |
| Suggests | MASS, class, nnet, glmnet, e1071, randomForest, plsgenomics, gbm, mgcv, corpcor, limma, st, mvtnorm |
| 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 | CMA_1.22.0.tar.gz |
| Windows Binary | CMA_1.22.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | CMA_1.22.0.tgz |
| Mac OS X 10.9 (Mavericks) | CMA_1.22.0.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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