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")
R Script | A modified spectral clustering method for clustering Flow Cytometry Data | |
Reference Manual |
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 |
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System Requirements | |
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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 |
Package Downloads Report | Download Stats |
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