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Integrated pathway-level analysis of transcriptomics and metabolomics data with IMPaLA

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons50371

Kamburov,  A.
Bioinformatics (Ralf Herwig), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Zitation

Kamburov, A., Cavill, R., Ebbels, T. M., Herwig, R., & Keun, H. C. (2011). Integrated pathway-level analysis of transcriptomics and metabolomics data with IMPaLA. Bioinformatics, 27(20), 2917-8. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21893519 http://bioinformatics.oxfordjournals.org/content/27/20/2917.full.pdf.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0010-78B8-3
Zusammenfassung
SUMMARY: Pathway-level analysis is a powerful approach enabling interpretation of post-genomic data at a higher level than that of individual biomolecules. Yet, it is currently hard to integrate more than one type of omics data in such an approach. Here, we present a web tool 'IMPaLA' for the joint pathway analysis of transcriptomics or proteomics and metabolomics data. It performs over-representation or enrichment analysis with user-specified lists of metabolites and genes using over 3000 pre-annotated pathways from 11 databases. As a result, pathways can be identified that may be disregulated on the transcriptional level, the metabolic level or both. Evidence of pathway disregulation is combined, allowing for the identification of additional pathways with changed activity that would not be highlighted when analysis is applied to any of the functional levels alone. The tool has been implemented both as an interactive website and as a web service to allow a programming interface. AVAILABILITY: The web interface of IMPaLA is available at http://impala.molgen.mpg.de. A web services programming interface is provided at http://impala.molgen.mpg.de/wsdoc. CONTACT: kamburov@molgen.mpg.de; r.cavill@imperial.ac.uk; h.keun@imperial.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.