title: Sebnif: an integrated bioinformatics pipeline for the identification of novel large intergenic noncoding RNAs (lincRNAs)--application in human skeletal muscle cells.
abstract: Ab initio assembly of transcriptome sequencing data has been widely used to identify large intergenic non-coding RNAs (lincRNAs), a novel class of gene regulators involved in many biological processes. To differentiate real lincRNA transcripts from thousands of assembly artifacts, a series of filtering steps such as filters of transcript length, expression level and coding potential, need to be applied. However, an easy-to-use and publicly available bioinformatics pipeline that integrates these filters is not yet available. Hence, we implemented sebnif, an integrative bioinformatics pipeline to facilitate the discovery of bona fide novel lincRNAs that are suitable for further functional characterization. Specifically, sebnif is the only pipeline that implements an algorithm for identifying high-quality single-exonic lincRNAs that were often omitted in many studies. To demonstrate the usage of sebnif, we applied it on a real biological RNA-seq dataset from Human Skeletal Muscle Cells (HSkMC) and built a novel lincRNA catalog containing 917 highly reliable lincRNAs. Sebnif is available at http://sunlab.lihs.cuhk.edu.hk/sebnif/.
authors.affiliation: Department of Chemical Pathology, Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR, China.
authors.forename: Kun
authors.initials: K
authors.lastname: Sun
authors.affiliation: Department of Obstetrics and Gynaecology, Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR, China.
authors.forename: Yu
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: Department of Obstetrics and Gynaecology, Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR, China.
authors.forename: Huating
authors.initials: H
authors.lastname: Wang
authors.affiliation: Department of Chemical Pathology, Li Ka Shing Institute of Health Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR, China.
authors.forename: Hao
authors.initials: H
authors.lastname: Sun
mesh_terms: D019295:Computational Biology / Q000379:methods*; D023281:Genomics; D006801:Humans; D058977:Molecular Sequence Annotation; D018485:Muscle Fibers, Skeletal / Q000378:metabolism*; D011401:Promoter Regions, Genetic; D022661:RNA, Untranslated / Q000235:genetics*; D015203:Reproducibility of Results; D012984:Software; D015533:Transcriptional Activation; D064878:Web Browser
chemical_list: D022661:RNA, Untranslated