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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("MAQCsubsetILM")
In most cases, you don't need to download the package archive at all.
MAQCsubsetILM
MAQC data subset for the Illumina platform
Bioconductor version: 3.0
MAQC data subset for the Illumina platform
Author: Laurent Gatto
Maintainer: Laurent Gatto <lg390 at cam.ac.uk>
Citation (from within R,
enter citation("MAQCsubsetILM")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("MAQCsubsetILM")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("MAQCsubsetILM")
| R Script | MAQCsubsetILM: MAQC data subset for the Illumina platform | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | ExperimentData, Microarray |
| Version | 1.3.1 |
| License | Artistic-2.0 |
| Depends | R (>= 2.10), Biobase(>= 2.5.5), lumi |
| Imports | |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | MAQCsubsetILM_1.3.1.tar.gz |
| Windows Binary | MAQCsubsetILM_1.3.1.zip |
| Mac OS X 10.6 (Snow Leopard) | MAQCsubsetILM_1.3.1.tgz |
| Mac OS X 10.9 (Mavericks) | MAQCsubsetILM_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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