Bo Wang, Aziz Mezlini, Feyyaz Demir, Marc Fiume, Zhuowen Tu, Michael Brudno, Benjamin Haibe-Kains, Anna Goldenberg
Similarity Network Fusion takes multiple views of a network and fuses them together to construct an overall status matrix. The input to our algorithm can be feature vectors, pairwise distances, or pairwise similarities. The learned status matrix can then be used for retrieval, clustering, and classification.

A bivariate Gaussian genotype clustering and calling algorithm
for Illumina microarrays
Stephen W. Erickson, PhD, with contributions from Joshua
Callaway, MPH
Stephen W. Erickson, PhD <SErickson@uams.edu>
A bivariate Gaussian genotype clustering and calling
algorithm for Illumina microarrays, building on the package
'mclust'.  Pronounced snip-em-clust.

Bivariate Gaussian Genotype Clustering and Calling for Illumina
Microarrays
Bivariate Gaussian genotype clustering and calling for Illumina microarrays, building on the package 'mclust'. Pronounced snip-em-clust.

Stephen W. Erickson and Joshua C. Callaway
Bivariate Gaussian genotype clustering and calling for Illumina
microarrays, building on the package 'mclust'. Pronounced snip-em-clust.

Pooling DNA on SNP microarrays is a cost-effective way to carry out genome-wide association studies for heritable disorders or traits. The SNPMaP package provides formal SNPMaP objects and methods in R as a base for these analyses using Affymetrix genotyping arrays.
methods, SNPMaP.cdm, affxparser, R.huge, R.utils, R (>= 2.4.0)

methods, SNPMaP.cdm, affxparser, R.huge, R.utils, R (>=
2.10.0)

Annotation for SNP Microarrays and Pooling in R
Pooling DNA on SNP microarrays is a cost-effective way to carry out genome-wide association studies for heritable disorders or traits. The SNPMaP package provides formal SNPMaP objects and methods in R as a base for these analyses using Affymetrix genotyping arrays. The SNPMaP.cdm package provides cdm objects for the SNPMaP package.

Parallel Computing Toolset for genome-wide association studies
A high-performance computing package for relatedness,
linkage disequilibrium and principal component analysis in
GWAS.