Nease

A method for gene ontology subclassification of high-throughput gene expression data

Thomas W. Chittenden, Eleanor A. Howe, Jennifer M. Taylor, Jessica C. Mar, Martin J. Aryee, Harold Gómez, Razvan Sultana, John Braisted, Sarita J. Nair, John Quackenbush, Chris Holmes

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Summary: High-throughput technologies can identify genes whose expression profiles correlate with specific phenotypes; however, placing these genes into a biological context remains challenging. To help address this issue, we developed nested Expression Analysis Systematic Explorer (nEASE). nEASE complements traditional gene ontology enrichment approaches by determining statistically enriched gene ontology subterms within a list of genes based on co-annotation. Here, we overview an open-source software version of the nEASE algorithm. nEASE can be used either stand-alone or as part of a pathway discovery pipeline.

Original languageEnglish (US)
Article numberbts011
Pages (from-to)726-728
Number of pages3
JournalBioinformatics
Volume28
Issue number5
DOIs
StatePublished - Mar 2012
Externally publishedYes

Fingerprint

Gene Ontology
Gene Expression Data
Gene expression
High Throughput
Ontology
Genes
Throughput
Gene Expression
Transcriptome
Software
Gene
Technology
Phenotype
Gene Expression Profile
Open Source Software
Correlate
Annotation
Pathway
Complement
Pipelines

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computational Mathematics
  • Statistics and Probability
  • Medicine(all)

Cite this

Chittenden, T. W., Howe, E. A., Taylor, J. M., Mar, J. C., Aryee, M. J., Gómez, H., ... Holmes, C. (2012). Nease: A method for gene ontology subclassification of high-throughput gene expression data. Bioinformatics, 28(5), 726-728. [bts011]. https://doi.org/10.1093/bioinformatics/bts011

Nease : A method for gene ontology subclassification of high-throughput gene expression data. / Chittenden, Thomas W.; Howe, Eleanor A.; Taylor, Jennifer M.; Mar, Jessica C.; Aryee, Martin J.; Gómez, Harold; Sultana, Razvan; Braisted, John; Nair, Sarita J.; Quackenbush, John; Holmes, Chris.

In: Bioinformatics, Vol. 28, No. 5, bts011, 03.2012, p. 726-728.

Research output: Contribution to journalArticle

Chittenden, TW, Howe, EA, Taylor, JM, Mar, JC, Aryee, MJ, Gómez, H, Sultana, R, Braisted, J, Nair, SJ, Quackenbush, J & Holmes, C 2012, 'Nease: A method for gene ontology subclassification of high-throughput gene expression data', Bioinformatics, vol. 28, no. 5, bts011, pp. 726-728. https://doi.org/10.1093/bioinformatics/bts011
Chittenden TW, Howe EA, Taylor JM, Mar JC, Aryee MJ, Gómez H et al. Nease: A method for gene ontology subclassification of high-throughput gene expression data. Bioinformatics. 2012 Mar;28(5):726-728. bts011. https://doi.org/10.1093/bioinformatics/bts011
Chittenden, Thomas W. ; Howe, Eleanor A. ; Taylor, Jennifer M. ; Mar, Jessica C. ; Aryee, Martin J. ; Gómez, Harold ; Sultana, Razvan ; Braisted, John ; Nair, Sarita J. ; Quackenbush, John ; Holmes, Chris. / Nease : A method for gene ontology subclassification of high-throughput gene expression data. In: Bioinformatics. 2012 ; Vol. 28, No. 5. pp. 726-728.
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