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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("fabiaData")
In most cases, you don't need to download the package archive at all.
fabiaData
Data sets for FABIA (Factor Analysis for Bicluster Acquisition)
Bioconductor version: 3.0
Supplying gene expression data sets for the demos of the biclustering method "Factor Analysis for Bicluster Acquisition" (FABIA). The following three data sets are provided: A) breast cancer (van't Veer, Nature, 2002), B) multiple tissues (Su, PNAS, 2002), and C) diffuse large-B-cell lymphoma (Rosenwald, N Engl J Med, 2002).
Author: Sepp Hochreiter <hochreit at bioinf.jku.at>
Maintainer: Sepp Hochreiter <hochreit at bioinf.jku.at>
Citation (from within R,
enter citation("fabiaData")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("fabiaData")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("fabiaData")
| R Script | fabiaData: Manual for the R Package | |
| Reference Manual |
Details
| biocViews | Bioinformatics, Clustering, DifferentialExpression, ExperimentData, Microarray, MultipleComparisons, Statistics, Visualization |
| Version | 1.3.1 |
| License | LGPL (>= 2.1) |
| Depends | R (>= 2.10.0), Biobase |
| Imports | utils |
| LinkingTo | |
| Suggests | fabia |
| SystemRequirements | |
| Enhances | |
| URL | http://www.bioinf.jku.at/software/fabia/fabia.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 | fabiaData_1.3.1.tar.gz |
| Windows Binary | fabiaData_1.3.1.zip |
| Mac OS X 10.6 (Snow Leopard) | fabiaData_1.3.1.tgz |
| Mac OS X 10.9 (Mavericks) | fabiaData_1.3.1.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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