Evidence map›Paper›PMID 28289155›Full record

ArticleRNA (New York, N.Y.)2017

Comprehensive processing of high-throughput small RNA sequencing data including quality checking, normalization, and differential expression analysis using the UEA sRNA Workbench.

Matthew Beckers, Irina Mohorianu, Matthew Stocks, Christopher Applegate, Tamas Dalmay, Vincent Moulton

Abstract read
In one paragraph

Article in RNA (New York, N.Y.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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  15. miRToolsGallery: a tag-based and rankable microRNA bioinformatics resources database portal.Database : the journal of biological databases and curation · 2018
    Article
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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

6 authors.

Matthew BeckersSchool of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, United Kingdom.
Irina MohorianuSchool of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, United Kingdom.
Matthew StocksSchool of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, United Kingdom.
Christopher ApplegateSchool of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, United Kingdom.
Tamas DalmaySchool of Biological Sciences, University of East Anglia, Norwich, NR4 7TJ, United Kingdom.
Vincent MoultonSchool of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, United Kingdom.

Funding

Biotechnology and Biological Sciences Research Council BB/L003139/1Biotechnology and Biological Sciences Research Council BB/L021269/1
6 · The paper itself

Abstract

Recently, high-throughput sequencing (HTS) has revealed compelling details about the small RNA (sRNA) population in eukaryotes. These 20 to 25 nt noncoding RNAs can influence gene expression by acting as guides for the sequence-specific regulatory mechanism known as RNA silencing. The increase in sequencing depth and number of samples per project enables a better understanding of the role sRNAs play by facilitating the study of expression patterns. However, the intricacy of the biological hypotheses coupled with a lack of appropriate tools often leads to inadequate mining of the available data and thus, an incomplete description of the biological mechanisms involved. To enable a comprehensive study of differential expression in sRNA data sets, we present a new interactive pipeline that guides researchers through the various stages of data preprocessing and analysis. This includes various tools, some of which we specifically developed for sRNA analysis, for quality checking and normalization of sRNA samples as well as tools for the detection of differentially expressed sRNAs and identification of the resulting expression patterns. The pipeline is available within the UEA sRNA Workbench, a user-friendly software package for the processing of sRNA data sets. We demonstrate the use of the pipeline on a

Indexed as

Computational BiologyGene Expression RegulationHigh-Throughput Nucleotide SequencingRNA, Small UntranslatedSequence Analysis, RNASoftwareReproducibility of ResultsWorkflowRNA, Small Untranslateddifferential expressionhigh-throughput sequencing (HTS)microRNA (miRNA)normalizationsmall RNA (sRNA)UEA sRNA Workbench, quality checking

Identifiers

PMID28289155
PMCPMC5435855

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.