MeV

Application data
Biological application domain(s)	RNA-Seq
Principal bioinformatics method(s)	Clustering, Visualization, Classification, Differentially expressed gene identification
Maintained?	Yes
Licence	Artistic License

Summary: Visualization of genomic data, Differential Gene Expression based on DEGseq, DESeq and edgeR

"Error: no local variable "counter" was set." is not a number.

Description

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.

Links

• MeV Source code [ edit link ]
• MeV Homepage [ edit link ]

• Add a Link

References

none specified

To add a reference for MeV, enter the PubMed ID in the field below and click 'Add'.

 

[ edit box ]

Search for "MeV" in the SEQanswers forum / BioStar or:

Web Search	Wiki Sites	Scientific
Google. Bioinformatics journals Clusty	WikiPedia MetaBase BioPedia OpenWetWare bifx wiki	PubMed Europe PMC ScientificCommons.org