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fastseg

fastseg - a fast segmentation algorithm

Bioconductor version: 3.23 · Package version: 1.58.0

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.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("fastseg")

Details

MaintainerAlexander Blume <alex.gos90@gmail.com>
AuthorGuenter Klambauer [aut], Sonali Kumari [ctb], Alexander Blume [cre]
LicenseLGPL (>= 2.0)
URLhttp://www.bioinf.jku.at/software/fastseg/index.html
Bug Reportshttps://github.com/alexg9010/fastseg/issues
Downloads rank1538
Source branchRELEASE_3_23
biocViewsClassification, CopyNumberVariation, Software

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagefastseg_1.58.0.tar.gz
Windows binary (x86_64)fastseg_1.58.0.zip
macOS binary (arm64)fastseg_1.58.0.tgz
macOS binary (x86_64)fastseg_1.58.0.tgz
Dependencies

Depends: R (>= 2.13), GenomicRanges, Biobase

Imports: methods, graphics, grDevices, stats, BiocGenerics, S4Vectors, IRanges

Suggests: DNAcopy, BiocStyle, knitr

Reverse dependencies

Imports Me (1): methylKit