To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("fastseg")

In most cases, you don't need to download the package archive at all.

fastseg

fastseg - a fast segmentation algorithm

Bioconductor version: 2.14

fastseg implements a very fast and efficient segmentation algorithm. It has similar functionality as DNACopy (Olshen and Venkatraman 2004), but is considerably faster and more flexible. fastseg can segment data from DNA microarrays and data from next generation sequencing for example to detect copy number segments. Further it can segment data from RNA microarrays like tiling arrays to identify transcripts. Most generally, it can segment data given as a matrix or as a vector. Various data formats can be used as input to fastseg like expression set objects for microarrays or GRanges for sequencing data. The segmentation criterion of fastseg is based on a statistical test in a Bayesian framework, namely the cyber t-test (Baldi 2001). The speed-up arises from the facts, that sampling is not necessary in for fastseg and that a dynamic programming approach is used for calculation of the segments' first and higher order moments.

Author: Guenter Klambauer

Maintainer: Guenter Klambauer <fastseg at bioinf.jku.at>

Citation (from within R, enter citation("fastseg")):

Installation

To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("fastseg")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("fastseg")

 

PDF R Script fastseg: Manual for the R package
PDF   Reference Manual

Details

biocViews Classification, CopyNumberVariation, Software
Version 1.10.0
In Bioconductor since BioC 2.9 (R-2.14)
License LGPL (>= 2.0)
Depends R (>= 2.13), GenomicRanges, Biobase
Imports graphics, stats, IRanges, BiocGenerics
Suggests DNAcopy, oligo
System Requirements
URL http://www.bioinf.jku.at/software/fastseg/fastseg.html
Depends On Me
Imports Me
Suggests Me

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source fastseg_1.10.0.tar.gz
Windows Binary fastseg_1.10.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) fastseg_1.10.0.tgz
Mac OS X 10.9 (Mavericks) fastseg_1.10.0.tgz
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