Please use this identifier to cite or link to this item: doi:10.22028/D291-36014
Title: miEAA 2.0: integrating multi-species microRNA enrichment analysis and workflow management systems
Author(s): Kern, Fabian
Fehlmann, Tobias
Solomon, Jeffrey
Schwed, Louisa
Grammes, Nadja
Backes, Christina
Van Keuren-Jensen, Kendall
Craig, David Wesley
Meese, Eckart
Keller, Andreas
Language: English
Title: Nucleic Acids Research
Volume: 48
Issue: W1
Pages: W521–W528
Publisher/Platform: Oxford University Press
Year of Publication: 2020
DDC notations: 610 Medicine and health
Publikation type: Journal Article
Abstract: Gene set enrichment analysis has become one of the most frequently used applications in molecular biology research. Originally developed for gene sets, the same statistical principles are now available for all omics types. In 2016, we published the miRNA enrichment analysis and annotation tool (miEAA) for human precursor and mature miRNAs. Here, we present miEAA 2.0, supporting miRNA input from ten frequently investigated organisms. To facilitate inclusion of miEAA in workflow systems, we implemented an Application Programming Interface (API). Users can perform miRNA set enrichment analysis using either the web-interface, a dedicated Python package, or custom remote clients. Moreover, the number of category sets was raised by an order of magnitude. We implemented novel categories like annotation confidence level or localisation in biological compartments. In combination with the miRBase miRNA-version and miRNA-to-precursor converters, miEAA supports research settings where older releases of miRBase are in use. The web server also offers novel comprehensive visualizations such as heatmaps and running sum curves with background distributions. We demonstrate the new features with case studies for human kidney cancer, a biomarker study on Parkinson’s disease from the PPMI cohort, and a mouse model for breast cancer. The tool is freely accessible at: https://www.ccb.uni-saarland.de/mieaa2.
DOI of the first publication: 10.1093/nar/gkaa309
Link to this record: urn:nbn:de:bsz:291--ds-360141
hdl:20.500.11880/32810
http://dx.doi.org/10.22028/D291-36014
ISSN: 1362-4962
0305-1048
Date of registration: 19-Apr-2022
Description of the related object: Supplementary data
Related object: https://oup.silverchair-cdn.com/oup/backfile/Content_public/Journal/nar/48/W1/10.1093_nar_gkaa309/1/gkaa309_supplemental_files.zip?Expires=1653380945&Signature=Z68YTBLFCIsaXn2Yar9qNZaVKmUjOxKmlJ405oTtKtqGes1bwXPBAgBaAdhwq-9Fu1gSHAHdPc5WLfw-v0~qk6dF~Xqxd892SDZnEZeAlrzfA5ddBReX51LuoFv7M5toOlSGQYYUrCc5Gc4MGUD8qQSsPrmQPUSnKqMOP8oFtJBAS3xtGAhT2xICa0HgLf9w07fheG6HF2QLccYLOwZqpKRqiw8-O1rFtDWll5VsZs9Yo43qZcjLLYWqsEVYjEm2kPangt-3m-Kqm4klkXcXA7ZOmuM8SEPUnsv-QWOGiHeX1f~gV3YLA-YpsEpl6MpTJnEGZ3FdLJz-lMrRr1wecg__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA
Faculty: M - Medizinische Fakultät
Department: M - Humangenetik
M - Medizinische Biometrie, Epidemiologie und medizinische Informatik
Professorship: M - Univ.-Prof. Dr. Andreas Keller
M - Prof. Dr. Eckhart Meese
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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