Evidence map›Paper›PMID 28911107›Full record

ArticleNucleic acids research2017

Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs.

Tobias Fehlmann, Christina Backes, Mustafa Kahraman, Jan Haas, Nicole Ludwig, Andreas E Posch, Maximilian L Würstle, Matthias Hübenthal, Andre Franke, Benjamin Meder and 2 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Tobias FehlmannChair for Clinical Bioinformatics, Saarland University, Saarbrücken, Germany.
Christina BackesChair for Clinical Bioinformatics, Saarland University, Saarbrücken, Germany.
Mustafa KahramanChair for Clinical Bioinformatics, Saarland University, Saarbrücken, Germany.
Jan HaasDepartment of Internal Medicine III, University Hospital Heidelberg, Heidelberg, Germany.
Nicole LudwigDepartment of Human Genetics, Saarland University, Homburg, Germany.
Andreas E PoschAres Genetics GmbH, Vienna, Austria.
Maximilian L WürstleSiemens Healthcare GmbH, Strategy and Innovation, Erlangen, Germany.
Matthias HübenthalInstitute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany.
Andre FrankeInstitute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany.
Benjamin MederDepartment of Internal Medicine III, University Hospital Heidelberg, Heidelberg, Germany.
Eckart MeeseDepartment of Human Genetics, Saarland University, Homburg, Germany.
Andreas KellerChair for Clinical Bioinformatics, Saarland University, Saarbrücken, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

InternetComputational BiologyData Interpretation, StatisticalHigh-Throughput Nucleotide SequencingHumansMicroarray AnalysisMicroRNAsSequence Analysis, RNATranscriptomeValidation Studies as TopicMicroRNAs

Identifiers

PMID28911107
PMCPMC5587802

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.