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Assessing identity, redundancy and confounds in Gene Ontology annotations over time Gillis, Jesse; Pavlidis, Paul

Description

MOTIVATION:

The Gene Ontology (GO) is heavily used in systems biology, but the potential for redundancy, confounds with other data sources and problems with stability over time have been little explored.

RESULTS:

We report that GO annotations are stable over short periods, with 3% of genes not being most semantically similar to themselves between monthly GO editions. However, we find that genes can alter their 'functional identity' over time, with 20% of genes not matching to themselves (by semantic similarity) after 2 years. We further find that annotation bias in GO, in which some genes are more characterized than others, has declined in yeast, but generally increased in humans. Finally, we discovered that many entries in protein interaction databases are owing to the same published reports that are used for GO annotations, with 66% of assessed GO groups exhibiting this confound. We provide a case study to illustrate how this information can be used in analyses of gene sets and networks.

AVAILABILITY:

Data available at http://chibi.ubc.ca/assessGO.

Item Metadata

Title
Assessing identity, redundancy and confounds in Gene Ontology annotations over time
Creator
Gillis, Jesse; Pavlidis, Paul
Contributor
Cuthill, Melissa
Date Created
2013
Date Issued
2019-03-11
Description

MOTIVATION:

The Gene Ontology (GO) is heavily used in systems biology, but the potential for redundancy, confounds with other data sources and problems with stability over time have been little explored.

RESULTS:

We report that GO annotations are stable over short periods, with 3% of genes not being most semantically similar to themselves between monthly GO editions. However, we find that genes can alter their 'functional identity' over time, with 20% of genes not matching to themselves (by semantic similarity) after 2 years. We further find that annotation bias in GO, in which some genes are more characterized than others, has declined in yeast, but generally increased in humans. Finally, we discovered that many entries in protein interaction databases are owing to the same published reports that are used for GO annotations, with 66% of assessed GO groups exhibiting this confound. We provide a case study to illustrate how this information can be used in analyses of gene sets and networks.

AVAILABILITY:

Data available at http://chibi.ubc.ca/assessGO.
Subject
Medicine, Health and Life Sciences
Type
Dataset
Notes
http://hdl.handle.net/11272/10571
Date Available
2019-03-11
Provider
University of British Columbia Library
License
CC0 1.0
DOI
10.14288/1.0363907
URI
https://doi.org/10.5683/SP2/ZLJTVW
Publisher DOI
https://doi.org/10.5683/SP2/ZLJTVW
Rights URI
http://creativecommons.org/publicdomain/zero/1.0
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CC0 1.0