To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("annmap")
In most cases, you don't need to download the package archive at all.
annmap
Genome annotation and visualisation package pertaining to Affymetrix arrays and NGS analysis.
Bioconductor version: 2.14
annmap provides annotation mappings for Affymetrix exon arrays and coordinate based queries to support deep sequencing data analysis. Database access is hidden behind the API which provides a set of functions such as genesInRange(), geneToExon(), exonDetails(), etc. Functions to plot gene architecture and BAM file data are also provided. Underlying data are from Ensembl.
Author: Tim Yates <tyates at picr.man.ac.uk>
Maintainer: Tim Yates <tyates at picr.man.ac.uk>
Citation (from within R,
enter citation("annmap")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("annmap")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("annmap")
| R Script | annmap installation instruction | |
| R Script | annmap primer | |
| R Script | The Annmap Cookbook | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Annotation, Microarray, OneChannel, ReportWriting, Software, Transcription, Visualization |
| Version | 1.6.0 |
| In Bioconductor since | BioC 2.11 (R-2.15) |
| License | GPL-2 |
| Depends | R (>= 2.15.0), methods, GenomicRanges |
| Imports | DBI, RMySQL (>= 0.6-0), digest, Biobase, grid, lattice, Rsamtools, genefilter, IRanges, BiocGenerics |
| Suggests | RUnit, rjson, Gviz |
| System Requirements | |
| URL | http://annmap.cruk.manchester.ac.uk |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | annmap_1.6.0.tar.gz |
| Windows Binary | |
| Mac OS X 10.6 (Snow Leopard) | annmap_1.6.0.tgz |
| Mac OS X 10.9 (Mavericks) | |
| 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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