To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("SAGx")
In most cases, you don't need to download the package archive at all.
SAGx
Statistical Analysis of the GeneChip
Bioconductor version: 3.0
A package for retrieval, preparation and analysis of data from the Affymetrix GeneChip. In particular the issue of identifying differentially expressed genes is addressed.
Author: Per Broberg
Maintainer: Per Broberg, <pi.broberg at gmail.com>
Citation (from within R,
enter citation("SAGx")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("SAGx")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("SAGx")
| R Script | samroc - example | |
| Reference Manual |
Details
| biocViews | Clustering, DataImport, DifferentialExpression, Microarray, MultipleComparison, OneChannel, Preprocessing, Software |
| Version | 1.40.0 |
| In Bioconductor since | BioC 1.9 (R-2.4) |
| License | GPL-3 |
| Depends | R (>= 2.5.0), stats, multtest, methods |
| Imports | Biobase, stats4 |
| LinkingTo | |
| Suggests | KEGG.db, hu6800.db, MASS |
| SystemRequirements | |
| Enhances | |
| URL | http://home.swipnet.se/pibroberg/expression_hemsida1.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 | SAGx_1.40.0.tar.gz |
| Windows Binary | SAGx_1.40.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | SAGx_1.40.0.tgz |
| Mac OS X 10.9 (Mavericks) | SAGx_1.40.0.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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