title: Identification of Long Noncoding RNAs Associated to Human Disease Susceptibility.
abstract: Transcriptomic as well as in vivo studies have revealed the importance of several lncRNAs in many complex diseases including cancer, cardiovascular, and neurological disorders. In this protocol, we describe how to perform RNAseq data analysis to identify lncRNAs associated with disease states utilizing the open-source software CANEapp (application for Comprehensive automated Analysis of Next-generation sequencing Experiments).
authors.affiliation: Center for Therapeutic Innovation, Department of Psychiatry and Behavioral Sciences, University of Miami, Miller School of Medicine, 1501 NW 10th Ave., Miami, 33136, FL, USA. mmagistri@med.miami.edu.
authors.forename: Marco
authors.initials: M
authors.lastname: Magistri
authors.affiliation: Department of Psychiatry and Behavioral Sciences, Center for Therapeutic Innovation, Miller School of Medicine, University of Miami, 1501 NW 10th Ave., Miami, FL, 33136, USA.
authors.forename: Dmitry
authors.initials: D
authors.lastname: Velmeshev
mesh_terms: D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods; D005786:Gene Expression Regulation; D056726:Genetic Association Studies / Q000379:methods; D020022:Genetic Predisposition to Disease; D006801:Humans; D062085:RNA, Long Noncoding / Q000235:genetics*; D012984:Software; D059467:Transcriptome; D064878:Web Browser
chemical_list: D062085:RNA, Long Noncoding
keywords: CANEapp; Long noncoding RNAs (lncRNAs); RNA sequencing