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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("adSplit")
In most cases, you don't need to download the package archive at all.
adSplit
Annotation-Driven Clustering
Bioconductor version: 3.0
This package implements clustering of microarray gene expression profiles according to functional annotations. For each term genes are annotated to, splits into two subclasses are computed and a significance of the supporting gene set is determined.
Author: Claudio Lottaz, Joern Toedling
Maintainer: Claudio Lottaz <Claudio.Lottaz at klinik.uni-regensburg.de>
Citation (from within R,
enter citation("adSplit")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("adSplit")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("adSplit")
| R Script | Annotation-Driven Clustering | |
| Reference Manual |
Details
| biocViews | Clustering, Microarray, Software |
| Version | 1.36.0 |
| In Bioconductor since | BioC 1.8 (R-2.3) |
| License | GPL (>= 2) |
| Depends | R (>= 2.1.0), methods (>= 2.1.0) |
| Imports | AnnotationDbi, Biobase(>= 1.5.12), cluster (>= 1.9.1), GO.db(>= 1.8.1), graphics, grDevices, KEGG.db(>= 1.8.1), methods, multtest(>= 1.6.0), stats (>= 2.1.0) |
| LinkingTo | |
| Suggests | golubEsets(>= 1.0), vsn(>= 1.5.0), hu6800.db(>= 1.8.1) |
| SystemRequirements | |
| Enhances | |
| URL | http://compdiag.molgen.mpg.de/software/index.shtml |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | adSplit_1.36.0.tar.gz |
| Windows Binary | adSplit_1.36.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | adSplit_1.36.0.tgz |
| Mac OS X 10.9 (Mavericks) | adSplit_1.36.0.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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