Evidence map›Paper›PMID 22359495›Full record

ArticlePLoS computational biology2012

On the Use of Gene Ontology Annotations to Assess Functional Similarity among Orthologs and Paralogs: A Short Report.

Paul D Thomas, Valerie Wood, Christopher J Mungall, Suzanna E Lewis, Judith A Blake, Gene Ontology Consortium

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed
5.1field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

57 citing papers in PubMed, 126 citations in OpenAlex.

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  8. Defining the extent of gene function using ROC curvature.Bioinformatics (Oxford, England) · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 2 countries.

Paul D ThomasDivision of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, California, United States of America. go-discuss@lists.stanford.edu
Valerie Wood
Christopher J Mungall
Suzanna E Lewis
Judith A Blake
Gene Ontology Consortium
Lawrence Berkeley National Laboratory · USJackson Laboratory · USUniversity of Cambridge · GBUniversity of Southern California · US

Funding

Mouse Genome DatabaseU41HG000330 · NHGRI · JACKSON LABORATORY · PI BLAKE, JUDITH A, BULT, CAROL J · 2011 to 2020
$45.5M
Gene Ontology ConsortiumP41HG002273 · NHGRI · JACKSON LABORATORY · PI BLAKE, JUDITH A · 2004 to 2011
$27.4M
Development and Maintenance of PANTHER SoftwareR01GM081084 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMAS, PAUL D. · 2008 to 2010
$2.0M
NHGRI NIH HHS P41 HG002273NHGRI NIH HHS U41 HG000330NIGMS NIH HHS R01 GM081084
6 · The paper itself

Abstract

A recent paper (Nehrt et al., PLoS Comput. Biol. 7:e1002073, 2011) has proposed a metric for the "functional similarity" between two genes that uses only the Gene Ontology (GO) annotations directly derived from published experimental results. Applying this metric, the authors concluded that paralogous genes within the mouse genome or the human genome are more functionally similar on average than orthologous genes between these genomes, an unexpected result with broad implications if true. We suggest, based on both theoretical and empirical considerations, that this proposed metric should not be interpreted as a functional similarity, and therefore cannot be used to support any conclusions about the "ortholog conjecture" (or, more properly, the "ortholog functional conservation hypothesis"). First, we reexamine the case studies presented by Nehrt et al. as examples of orthologs with divergent functions, and come to a very different conclusion: they actually exemplify how GO annotations for orthologous genes provide complementary information about conserved biological functions. We then show that there is a global ascertainment bias in the experiment-based GO annotations for human and mouse genes: particular types of experiments tend to be performed in different model organisms. We conclude that the reported statistical differences in annotations between pairs of orthologous genes do not reflect differences in biological function, but rather complementarity in experimental approaches. Our results underscore two general considerations for researchers proposing novel types of analysis based on the GO: 1) that GO annotations are often incomplete, potentially in a biased manner, and subject to an "open world assumption" (absence of an annotation does not imply absence of a function), and 2) that conclusions drawn from a novel, large-scale GO analysis should whenever possible be supported by careful, in-depth examination of examples, to help ensure the conclusions have a justifiable biological basis.

Indexed as

Genome, HumanAlgorithmsAnimalsCell NucleusComputational BiologyGenomeGenomicsHumansMiceModels, GeneticModels, StatisticalMolecular BiologyMolecular Sequence AnnotationPhosphorylationProbabilitySpecies Specificity

Identifiers

PMID22359495
PMCPMC3280971
OpenAlexW2145189015

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.