Evidence map›Paper›PMID 28830358›Full record

ArticleBMC genomics2017

unitas: the universal tool for annotation of small RNAs.

Daniel Gebert, Charlotte Hewel, David Rosenkranz

Abstract read
In one paragraph

Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers.

0numbers the graph read from it
0cells of the map it votes in
78citing 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

78 citing papers in PubMed.

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  16. Diverse plant RNAs coatProceedings of the National Academy of Sciences of the United States of America · 2025
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18 more citing papers are in PubMed but not listed here.

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

3 authors.

Daniel GebertInstitute of Organismic and Molecular Evolutionary Biology, Anthropology, Johannes Gutenberg University, 55099, Mainz, Germany.
Charlotte HewelInstitute of Organismic and Molecular Evolutionary Biology, Anthropology, Johannes Gutenberg University, 55099, Mainz, Germany.
David RosenkranzInstitute of Organismic and Molecular Evolutionary Biology, Anthropology, Johannes Gutenberg University, 55099, Mainz, Germany. rosenkranz@uni-mainz.de.ORCID http://orcid.org/0000-0001-5781-6201

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNext generation sequencing is a key technique in small RNA biology research that has led to the discovery of functionally different classes of small non-coding RNAs in the past years. However, reliable annotation of the extensive amounts of small non-coding RNA data produced by high-throughput sequencing is time-consuming and requires robust bioinformatics expertise. Moreover, existing tools have a number of shortcomings including a lack of sensitivity under certain conditions, limited number of supported species or detectable sub-classes of small RNAs.

resultsHere we introduce unitas, an out-of-the-box ready software for complete annotation of small RNA sequence datasets, supporting the wide range of species for which non-coding RNA reference sequences are available in the Ensembl databases (currently more than 800). unitas combines high quality annotation and numerous analysis features in a user-friendly manner. A complete annotation can be started with one simple shell command, making unitas particularly useful for researchers not having access to a bioinformatics facility. Noteworthy, the algorithms implemented in unitas are on par or even outperform comparable existing tools for small RNA annotation that map to publicly available ncRNA databases.

conclusionsunitas brings together annotation and analysis features that hitherto required the installation of numerous different bioinformatics tools which can pose a challenge for the non-expert user. With this, unitas overcomes the problem of read normalization. Moreover, the high quality of sequence annotation and analysis, paired with the ease of use, make unitas a valuable tool for researchers in all fields connected to small RNA biology.

Indexed as

HeLa CellsHigh-Throughput Nucleotide SequencingHumansMolecular Sequence AnnotationRNA, Small UntranslatedRNA, Small UntranslatedmiRNAphasiRNApiRNARNA-seq data analysisSmall non-coding RNAstRNA-derived fragments (tRFs)

Identifiers

PMID28830358
PMCPMC5567656

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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.