- Home
- Bioconductor 2.14
- Software Packages
- sagenhaft
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("sagenhaft")
In most cases, you don't need to download the package archive at all.
sagenhaft
Collection of functions for reading and comparing SAGE libraries
Bioconductor version: 2.14
This package implements several functions useful for analysis of gene expression data by sequencing tags as done in SAGE (Serial Analysis of Gene Expressen) data, i.e. extraction of a SAGE library from sequence files, sequence error correction, library comparison. Sequencing error correction is implementing using an Expectation Maximization Algorithm based on a Mixture Model of tag counts.
Author: Tim Beissbarth <beissbarth at wehi.edu.au>, with contributions from Gordon Smyth <smyth at wehi.edu.au> and Lavinia Hyde <hyde at wehi.edu.au>.
Maintainer: Tim Beissbarth <beissbarth at wehi.edu.au>
Citation (from within R,
enter citation("sagenhaft")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("sagenhaft")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("sagenhaft")
| R Script | SAGEnhaft | |
| Reference Manual |
Details
| biocViews | SAGE, Software |
| Version | 1.34.0 |
| In Bioconductor since | BioC 1.6 (R-2.1) or earlier |
| License | GPL (>= 2) |
| Depends | R (>= 2.10), SparseM (>= 0.73), methods |
| Imports | graphics, methods, SparseM, stats, utils |
| Suggests | |
| System Requirements | |
| URL | http://tagcalling.mbgproject.org |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | sagenhaft_1.34.0.tar.gz |
| Windows Binary | sagenhaft_1.34.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | sagenhaft_1.34.0.tgz |
| Mac OS X 10.9 (Mavericks) | sagenhaft_1.34.0.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
Post questions about Bioconductor packages to our mailing lists. Read the posting guide before posting!
Contact us: support.bioconductor.org
Hosting provided by Fred Hutchinson Cancer Research Center
Copyright © 2003 - 2014
