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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("genoset")
In most cases, you don't need to download the package archive at all.
genoset
Provides classes similar to ExpressionSet for copy number analysis
Bioconductor version: 2.14
Load, manipulate, and plot copynumber and BAF data. GenoSet class extends eSet by adding a "locData" slot for a RangedData or GRanegs object. This object contains feature genome location data and provides for efficient subsetting on genome location. CNSet and BAFSet extend GenoSet and require assayData matrices for Copy Number (cn) or Log-R Ratio (lrr) and B-Allele Frequency (baf) data. Implements and provides convenience functions for processing of copy number and B-Allele Frequency data.
Author: Peter M. Haverty
Maintainer: Peter M. Haverty <phaverty at gene.com>
Citation (from within R,
enter citation("genoset")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("genoset")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("genoset")
| R Script | genoset | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | CopyNumberVariation, DataRepresentation, Infrastructure, Microarray, SNP, Software |
| Version | 1.16.2 |
| In Bioconductor since | BioC 2.8 (R-2.13) |
| License | Artistic-2.0 |
| Depends | R (>= 2.10), BiocGenerics(>= 0.1.6), Biobase(>= 2.15.1), IRanges, GenomicRanges |
| Imports | methods, graphics |
| Suggests | RUnit, DNAcopy, stats, BSgenome, Biostrings |
| System Requirements | |
| URL | |
| Depends On Me | VegaMC |
| Imports Me | methyAnalysis |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | genoset_1.16.2.tar.gz |
| Windows Binary | genoset_1.16.2.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | genoset_1.16.2.tgz |
| Mac OS X 10.9 (Mavericks) | genoset_1.16.2.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
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