Carlevaro-Fita, Joana; Liu, Leibo; Zhou, Yuan; Zhang, Shan; Chouvardas, Panagiotis; Johnson, Rory; Li, Jianwei (2019). LnCompare: gene set feature analysis for human long non-coding RNAs. Nucleic acids research, 47(W1), W523-W529. Oxford University Press 10.1093/nar/gkz410
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Interest in the biological roles of long noncoding RNAs (lncRNAs) has resulted in growing numbers of studies that produce large sets of candidate genes, for example, differentially expressed between two conditions. For sets of protein-coding genes, ontology and pathway analyses are powerful tools for generating new insights from statistical enrichment of gene features. Here we present the LnCompare web server, an equivalent resource for studying the properties of lncRNA gene sets. The Gene Set Feature Comparison mode tests for enrichment amongst a panel of quantitative and categorical features, spanning gene structure, evolutionary conservation, expression, subcellular localization, repetitive sequences and disease association. Moreover, in Similar Gene Identification mode, users may identify other lncRNAs by similarity across a defined range of features. Comprehensive results may be downloaded in tabular and graphical formats, in addition to the entire feature resource. LnCompare will empower researchers to extract useful hypotheses and candidates from lncRNA gene sets.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Clinic of Medical Oncology 04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) |
UniBE Contributor: |
Carlevaro Fita, Joana, Chouvardas, Panagiotis, Johnson, Rory Baldwin |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
0305-1048 |
Publisher: |
Oxford University Press |
Language: |
English |
Submitter: |
Rebeka Gerber |
Date Deposited: |
05 Nov 2019 08:34 |
Last Modified: |
05 Dec 2022 15:31 |
Publisher DOI: |
10.1093/nar/gkz410 |
PubMed ID: |
31147707 |
BORIS DOI: |
10.7892/boris.134311 |
URI: |
https://boris.unibe.ch/id/eprint/134311 |