Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs. Fehlmann, T., Backes, C., Kahraman, M., Haas, J., Ludwig, N., Posch, A. E, Würstle, M. L, Hübenthal, M., Franke, A., Meder, B., Meese, E., & Keller, A. Nucleic acids research, 45:8731–8744, September, 2017.
doi  abstract   bibtex   
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.
@Article{Fehlmann2017a,
  author          = {Fehlmann, Tobias and Backes, Christina and Kahraman, Mustafa and Haas, Jan and Ludwig, Nicole and Posch, Andreas E and Würstle, Maximilian L and Hübenthal, Matthias and Franke, Andre and Meder, Benjamin and Meese, Eckart and Keller, Andreas},
  title           = {Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs.},
  journal         = {Nucleic acids research},
  year            = {2017},
  volume          = {45},
  pages           = {8731--8744},
  month           = sep,
  issn            = {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.},
  chemicals       = {MicroRNAs},
  citation-subset = {IM},
  completed       = {2017-11-07},
  country         = {England},
  doi             = {10.1093/nar/gkx595},
  issn-linking    = {0305-1048},
  issue           = {15},
  keywords        = {Computational Biology, methods, statistics & numerical data; Data Interpretation, Statistical; High-Throughput Nucleotide Sequencing, methods, statistics & numerical data; Humans; Internet; MicroRNAs, analysis, genetics; Microarray Analysis, methods; Sequence Analysis, RNA, methods, statistics & numerical data; Transcriptome; Validation Studies as Topic},
  nlm-id          = {0411011},
  owner           = {NLM},
  pii             = {3956630},
  pmc             = {PMC5587802},
  pmid            = {28911107},
  pubmodel        = {Print},
  pubstatus       = {ppublish},
  revised         = {2017-11-07},
}
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