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Short description:
Please summarise the application in a few sentences. Avoid links here. Visualisation of genomic data, Differential Gene Expression based on DEGseq, DESeq and edgeR
Software version:
Biological application domain(s) (Phylogenetics, Genomics, ...):
RNA-Seq,
Principal bioinformatics method(s) (Assembly, Mapping, ...):
Sequence clustering, Visualisation, Classification, Differential expression analysis,
Technology (Sanger, Illumina, 454, SOLiD, Ion Torrent, ...):
Interface (Command line, Web UI, Desktop GUI, SOAP WS, HTTP WS, API, QL):
Resource type (Command-line tool, Web application, Desktop application, Script, Suite, Workbench, Database portal, Workflow, Plug-in, Library, Web API, Web service, SPARQL endpoint):
== Description == <!-- Describe the application in the space below --> MeV is a desktop application for the analysis, visualization and data-mining of large-scale genomic data. It is a versatile microarray tool, incorporating sophisticated algorithms for clustering, visualization, classification, statistical analysis and biological theme discovery. Thousands of biologists have downloaded and used MeV to examine their data with an easy-to-use, graphical interface. MeV generates informative and interrelated displays of expression and annotation data from single or multiple experiments. A huge array of alrogithms are included in MeV modules, and are available at a button-click, such as K-means clustering, Hierarchical clustering, t-Tests, Significance Analysis of Microarrays, Gene Set Enrichment Analysis, and EASE. Extensive documentation is available for helping new users get started with MeV. A Quickstart Guide provides the tutorial a brand new person will need to get their first dataset loaded and displayed in the program. Returning MEV users will want to check out the release notes to see what new features are available in the latest versions of the program. Tutorials have been written about several of MeV's more involved features. <!-- -->
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