GenePattern Suites

ClusteringSuite
Clustering modules partition a gene expression dataset into clusters such that the gene expression data in each cluster share common expression traits based on the distance measure used.
 
GeneListSelectionSuite
Gene List Selection modules include several algorithms to determine features (genes) that are most closely correlated with known class templates (e.g. tumour vs normal) and the significance of the correlation.
 
LuGetzMiska.Nature.2005.Suite
Pipelines used in the Lu, Getz, Miska paper "MicroRNA expression profiles classify human cancers" available at http://www.nature.com/nature/journal/v435/n7043/full/nature03702.html
 
MultiplotSuite
consists three Multiplot modules: MultiplotPreprocess, Multiplot and MultiplotExtractor.
 
PredictionSuite
Prediction modules perform two step analyses on gene expression datasets where the first step is to create a model based on data of known class (train dataset) and the second step is to predict the class of additional samples (test dataset). Most methods require seperate test and train datasets while cross validation (XValidation) methods use a single dataset to create a model using leave-one-out cross-validation by iteratively leaving one sample out and constructing a training model on the remaining data and then testing the model on the left-out sample.
 
PredictionSuite
Prediction modules perform two step analyses on gene expression datasets where the first step is to create a model based on data of known class (train dataset) and the second step is to predict the class of additional samples (test dataset). Most methods require seperate test and train datasets while cross validation (XValidation) methods use a single dataset to create a model using leave-one-out cross-validation by iteratively leaving one sample out and constructing a training model on the remaining data and then testing the model on the left-out sample.
 
ProteomicsSuite
Peak detection, noise subtraction, peak matching, and more for advanced analysis of MALDI, SELDI, and LC-MS data.
 
RNA-seq
A suite of modules and pipelines to support RNA-seq analyses, including short-read mapping, identification of splice junctions, transcript and isoform detection, quantitation, and differential expression.
 
SNP Analysis
The SNP Analysis suite contains modules for the preprocessing, analysis and visualization of SNP data.