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Status: Bibliographieeintrag

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Verfasst von:Fehlmann, Tobias [VerfasserIn]   i
 Haas, Jan [VerfasserIn]   i
 Meder, Benjamin [VerfasserIn]   i
Titel:Web-based NGS data analysis using miRMaster
Titelzusatz:a large-scale meta-analysis of human miRNAs
Verf.angabe:Tobias Fehlmann, Christina Backes, Mustafa Kahraman, Jan Haas, Nicole Ludwig, Andreas E. Posch, Maximilian L. Würstle, Matthias Hübenthal, Andre Franke, Benjamin Meder, Eckart Meese, and Andreas Keller
E-Jahr:2017
Jahr:6 September 2017
Umfang:14 S.
Fussnoten:Gesehen am 14.11.2018
Titel Quelle:Enthalten in: Nucleic acids research
Ort Quelle:Oxford : Oxford Univ. Press, 1974
Jahr Quelle:2017
Band/Heft Quelle:45(2017), 15, Seite 8731-8744
ISSN Quelle:1362-4962
Abstract:The analysis of small RNA NGS data together with the discovery of new small RNAs is among the foremost challenges in life science. For the analysis of raw high-throughput sequencing data we implemented the fast, accurate and comprehensive web-based tool miRMaster. Our toolbox provides a wide range of modules for quantification of miRNAs and other non-coding RNAs, discovering new miRNAs, isomiRs, mutations, exogenous RNAs and motifs. Use-cases comprising hundreds of samples are processed in less than 5 h with an accuracy of 99.4%. An integrative analysis of small RNAs from 1836 data sets (20 billion reads) indicated that context-specific miRNAs (e.g. miRNAs present only in one or few different tissues / cell types) still remain to be discovered while broadly expressed miRNAs appear to be largely known. In total, our analysis of known and novel miRNAs indicated nearly 22 000 candidates of precursors with one or two mature forms. Based on these, we designed a custom microarray comprising 11 872 potential mature miRNAs to assess the quality of our prediction. MiRMaster is a convenient-to-use tool for the comprehensive and fast analysis of miRNA NGS data. In addition, our predicted miRNA candidates provided as custom array will allow researchers to perform in depth validation of candidates interesting to them.
DOI:doi:10.1093/nar/gkx595
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: http://dx.doi.org/10.1093/nar/gkx595
 DOI: https://doi.org/10.1093/nar/gkx595
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Computational Biology
 Data Interpretation, Statistical
 High-Throughput Nucleotide Sequencing
 Humans
 Internet
 Microarray Analysis
 MicroRNAs
 Sequence Analysis, RNA
 Transcriptome
 Validation Studies as Topic
K10plus-PPN:158370261X
Verknüpfungen:→ Zeitschrift

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