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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("breastCancerMAINZ")
In most cases, you don't need to download the package archive at all.
breastCancerMAINZ
Gene expression dataset published by Schmidt et al. [2008] (MAINZ).
Bioconductor version: 3.0
Gene expression data from the breast cancer study published by Schmidt et al. in 2008, provided as an eSet.
Author: Markus Schroeder, Benjamin Haibe-Kains, Aedin Culhane, Christos Sotiriou, Gianluca Bontempi, John Quackenbush
Maintainer: Markus Schroeder <mschroed at jimmy.harvard.edu>, Benjamin Haibe-Kains <bhaibeka at jimmy.harvard.edu>
Citation (from within R,
enter citation("breastCancerMAINZ")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("breastCancerMAINZ")
Documentation
| Reference Manual |
Details
| biocViews | Cancer, ExperimentData, GeneExpression, Microarray |
| Version | 1.3.1 |
| License | Artistic-2.0 |
| Depends | R (>= 2.5.0) |
| Imports | |
| LinkingTo | |
| Suggests | survcomp, genefu, Biobase |
| SystemRequirements | |
| Enhances | |
| URL | http://compbio.dfci.harvard.edu/ |
| Depends On Me | |
| Imports Me | |
| Suggests Me | DART, genefu, MineICA |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | breastCancerMAINZ_1.3.1.tar.gz |
| Windows Binary | breastCancerMAINZ_1.3.1.zip |
| Mac OS X 10.6 (Snow Leopard) | breastCancerMAINZ_1.3.1.tgz |
| Mac OS X 10.9 (Mavericks) | breastCancerMAINZ_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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