Evidence map›Paper›PMID 28053114›Full record

ArticleNucleic acids research2017

FEELnc: a tool for long non-coding RNA annotation and its application to the dog transcriptome.

Valentin Wucher, Fabrice Legeai, Benoît Hédan, Guillaume Rizk, Lætitia Lagoutte, Tosso Leeb, Vidhya Jagannathan, Edouard Cadieu, Audrey David, Hannes Lohi and 12 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 301 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
301citing papers in PubMed, 2 pooled it
–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

301 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  10. Long non-coding RNAs link DNA methylation to immune regulatory networks in bovine subclinical mastitis.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
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241 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

22 authors.

Valentin WucherInstitut Génétique et Développement de Rennes, CNRS, UMR6290, University Rennes1, Rennes, Cedex 35043, France.
Fabrice LegeaiIGEPP, BIPAA, INRA, Campus Beaulieu, Le Rheu 35653, France.
Benoît HédanInstitut Génétique et Développement de Rennes, CNRS, UMR6290, University Rennes1, Rennes, Cedex 35043, France.
Guillaume RizkInstitut National de Recherche en Informatique et en Automatique, Institut de Recherche en Informatique et Systèmes Aléatoires, Genscale, Campus Beaulieu, Rennes 35042, France.
Lætitia LagoutteInstitut Génétique et Développement de Rennes, CNRS, UMR6290, University Rennes1, Rennes, Cedex 35043, France.
Tosso LeebInstitute of Genetics, Vetsuisse Faculty, University of Bern, Bern 3001, Switzerland.
Vidhya JagannathanInstitute of Genetics, Vetsuisse Faculty, University of Bern, Bern 3001, Switzerland.
Edouard CadieuInstitut Génétique et Développement de Rennes, CNRS, UMR6290, University Rennes1, Rennes, Cedex 35043, France.
Audrey DavidIGEPP, BIPAA, INRA, Campus Beaulieu, Le Rheu 35653, France.
Hannes LohiDepartment of Veterinary Biosciences and Research Programs Unit, Molecular Neurology, University of Helsinki, PO Box 63, Helsinki 00014, Finland.
Susanna CireraDepartment of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 1870, Denmark.
Merete FredholmDepartment of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 1870, Denmark.
Nadine BotherelInstitut Génétique et Développement de Rennes, CNRS, UMR6290, University Rennes1, Rennes, Cedex 35043, France.
Peter A J LeegwaterDepartment of Clinical Sciences of Companion Animals, Faculty of Veterinary Medicine, Utrecht University, Utrecht 3584CM, the Netherlands.
Céline Le BéguecInstitut Génétique et Développement de Rennes, CNRS, UMR6290, University Rennes1, Rennes, Cedex 35043, France.
Hille FietenDepartment of Clinical Sciences of Companion Animals, Faculty of Veterinary Medicine, Utrecht University, Utrecht 3584CM, the Netherlands.
Jeremy JohnsonBroad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Jessica AlföldiBroad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Catherine AndréInstitut Génétique et Développement de Rennes, CNRS, UMR6290, University Rennes1, Rennes, Cedex 35043, France.
Kerstin Lindblad-TohBroad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Christophe HitteInstitut Génétique et Développement de Rennes, CNRS, UMR6290, University Rennes1, Rennes, Cedex 35043, France.
Thomas DerrienInstitut Génétique et Développement de Rennes, CNRS, UMR6290, University Rennes1, Rennes, Cedex 35043, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whole transcriptome sequencing (RNA-seq) has become a standard for cataloguing and monitoring RNA populations. One of the main bottlenecks, however, is to correctly identify the different classes of RNAs among the plethora of reconstructed transcripts, particularly those that will be translated (mRNAs) from the class of long non-coding RNAs (lncRNAs). Here, we present FEELnc (FlExible Extraction of LncRNAs), an alignment-free program that accurately annotates lncRNAs based on a Random Forest model trained with general features such as multi k-mer frequencies and relaxed open reading frames. Benchmarking versus five state-of-the-art tools shows that FEELnc achieves similar or better classification performance on GENCODE and NONCODE data sets. The program also provides specific modules that enable the user to fine-tune classification accuracy, to formalize the annotation of lncRNA classes and to identify lncRNAs even in the absence of a training set of non-coding RNAs. We used FEELnc on a real data set comprising 20 canine RNA-seq samples produced by the European LUPA consortium to substantially expand the canine genome annotation to include 10 374 novel lncRNAs and 58 640 mRNA transcripts. FEELnc moves beyond conventional coding potential classifiers by providing a standardized and complete solution for annotating lncRNAs and is freely available at https://github.com/tderrien/FEELnc.

Indexed as

GenomeSoftwareTranscriptomeAnimalsBenchmarkingDecision TreesDogsGene Expression RegulationHumansMiceMolecular Sequence AnnotationOpen Reading FramesRNA, Long NoncodingRNA, MessengerSequence Analysis, RNARNA, Long NoncodingRNA, Messenger

Identifiers

PMID28053114
PMCPMC5416892

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.