ErmineJ Analyze gene sets with this application.
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ErmineJ Ranking & Summary

ErmineJ Tags

analyzer analysis expression gene expression gene analyze application sets analyze gene set find gene set extract gene subset gene subset searcher grab gene subset view gene data display gene data analyze gene expression gene correlation correlate gene analyze gene gene organization gene visualization compare gene gene comparer gene pattern candidate gene simulate gene mutation gene adjacency gene annotation Gene Ontology database Gene Ontology create gene network gene network generator gene information gene product association gene disease association gene identifiers translator gene function prediction gene identification analyze gene structure gene structure analyzer gene mapper gene order comparison compare gene order gene content derived analyze protein-coding gene gene selection analyze genetic data sets analyze 16S rRNA gene sequence ancestral gene cluster gene cluster calculator ancestral gene gene cluster analyze gene data gene data analysis expression micro-array data analyze gene markers gene transfer simulate gene network growing gene duplication analyze gene frequency data estimate gene diversities test gene diversities Gene Diversity Gene Sequence gene-gene interaction Gene Sequence Name gene clusters reliability analyze modifier gene map disease gene visualize gene explore gene view gene

ErmineJ Description

ErmineJ is a handy, easy to use tool designed to help you perform analysis of gene sets in expression micro-array data or other genome-wide data that results in rankings of genes. A typical goal is to determine whether particular biological pathways are "doing something interesting" in the data. The software is designed to be used by biologists with little or no informatics background. Main features: Implementation of multiple methods for gene set analysis: Over-representation analysis A resampling-based method that uses gene scores A rank-based method that uses gene scores A resampling-based method that uses correlation between gene expression profiles (a type of "cluster-enrichment" analysis). Gene sets receive statistical scores (p-values), and multiple test correction is supported. Support of the Gene Ontology terminology; users can choose which aspects to analyze. User files use simple text formats. Users can modify gene sets or create new ones. The results can be visualized within the software. It is simple to compare multiple analyses of the same data set with different settings. User-definable hyperlinks are provided to external sites to allow more efficient browsing of the results. For programmers, there is a command line interface as well as a simple application programming interface that can be used to plug ermineJ functionality into your own code

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