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

Wucher, Valentin; Legeai, Fabrice; Hédan, Benoît; Rizk, Guillaume; Lagoutte, Lætitia; Leeb, Tosso; Jagannathan, Vidhya; Cadieu, Edouard; David, Audrey; Lohi, Hannes; Cirera, Susanna; Fredholm, Merete; Botherel, Nadine; Leegwater, Peter A J; Le Béguec, Céline; Fieten, Hille; Johnson, Jeremy; Alföldi, Jessica; André, Catherine; Lindblad-Toh, Kerstin; ... (2017). FEELnc: a tool for long non-coding RNA annotation and its application to the dog transcriptome. Nucleic acids research, 45(8), e57. Information Retrieval Ltd. 10.1093/nar/gkw1306

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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.

Item Type:

Journal Article (Original Article)

Division/Institute:

05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH)
05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH) > Institute of Genetics

UniBE Contributor:

Leeb, Tosso and Jagannathan, Vidya

Subjects:

500 Science > 570 Life sciences; biology
500 Science > 590 Animals (Zoology)
600 Technology > 610 Medicine & health

ISSN:

0305-1048

Publisher:

Information Retrieval Ltd.

Language:

English

Submitter:

Tosso Leeb

Date Deposited:

06 Jul 2017 15:18

Last Modified:

07 Jul 2017 14:09

Publisher DOI:

10.1093/nar/gkw1306

PubMed ID:

28053114

BORIS DOI:

10.7892/boris.93476

URI:

https://boris.unibe.ch/id/eprint/93476

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