SamSPECTRAL

Identifies cell population in flow cytometry data.

Bioconductor version: Release (2.12)

Samples large data such that spectral clustering is possible while preserving density information in edge weights. More specifically, given a matrix of coordinates as input, SamSPECTRAL first builds the communities to sample the data points. Then, it builds a graph and after weighting the edges by conductance computation, the graph is passed to a classic spectral clustering algorithm to find the spectral clusters. The last stage of SamSPECTRAL is to combine the spectral clusters. The resulting "connected components" estimate biological cell populations in the data sample. For instructions on manual installation, refer to the PDF file provided in the following documentation.

Author: Habil Zare and Parisa Shooshtari

Maintainer: Habil Zare <zare at u.washington.edu>

To install this package, start R and enter:

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

To cite this package in a publication, start R and enter:

    citation("SamSPECTRAL")

Documentation

PDF R Script A modified spectral clustering method for clustering Flow Cytometry Data
PDF   Reference Manual

Details

biocViews Bioinformatics, Cancer, CellBiology, Clustering, FlowCytData, FlowCytometry, HIV, Software, StemCells
Version 1.14.1
In Bioconductor since BioC 2.6 (R-2.11)
License GPL (>= 2)
Depends R (>= 2.10)
Imports methods
Suggests
System Requirements
URL
Depends On Me
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Package Downloads

Package Source SamSPECTRAL_1.14.1.tar.gz
Windows Binary SamSPECTRAL_1.14.1.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) SamSPECTRAL_1.14.1.tgz
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