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An unbiased evaluation of gene prioritization tools

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An unbiased evaluation of gene prioritization tools. / Börnigen, Daniela; Tranchevent, Léon-Charles; Bonachela-Capdevila, Francisco; Devriendt, Koenraad; De Moor, Bart; De Causmaecker, Patrick; Moreau, Yves.

In: BIOINFORMATICS, Vol. 28, No. 23, 01.12.2012, p. 3081-3088.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Börnigen, D, Tranchevent, L-C, Bonachela-Capdevila, F, Devriendt, K, De Moor, B, De Causmaecker, P & Moreau, Y 2012, 'An unbiased evaluation of gene prioritization tools', BIOINFORMATICS, vol. 28, no. 23, pp. 3081-3088. https://doi.org/10.1093/bioinformatics/bts581

APA

Börnigen, D., Tranchevent, L-C., Bonachela-Capdevila, F., Devriendt, K., De Moor, B., De Causmaecker, P., & Moreau, Y. (2012). An unbiased evaluation of gene prioritization tools. BIOINFORMATICS, 28(23), 3081-3088. https://doi.org/10.1093/bioinformatics/bts581

Vancouver

Börnigen D, Tranchevent L-C, Bonachela-Capdevila F, Devriendt K, De Moor B, De Causmaecker P et al. An unbiased evaluation of gene prioritization tools. BIOINFORMATICS. 2012 Dec 1;28(23):3081-3088. https://doi.org/10.1093/bioinformatics/bts581

Bibtex

@article{5ded1ba45f3e4585828a1272c56d8a80,
title = "An unbiased evaluation of gene prioritization tools",
abstract = "MOTIVATION: Gene prioritization aims at identifying the most promising candidate genes among a large pool of candidates-so as to maximize the yield and biological relevance of further downstream validation experiments and functional studies. During the past few years, several gene prioritization tools have been defined, and some of them have been implemented and made available through freely available web tools. In this study, we aim at comparing the predictive performance of eight publicly available prioritization tools on novel data. We have performed an analysis in which 42 recently reported disease-gene associations from literature are used to benchmark these tools before the underlying databases are updated.RESULTS: Cross-validation on retrospective data provides performance estimate likely to be overoptimistic because some of the data sources are contaminated with knowledge from disease-gene association. Our approach mimics a novel discovery more closely and thus provides more realistic performance estimates. There are, however, marked differences, and tools that rely on more advanced data integration schemes appear more powerful.CONTACT: yves.moreau@esat.kuleuven.beSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.",
keywords = "Databases, Genetic, Genetic Association Studies, Humans, Internet, Comparative Study, Journal Article, Research Support, Non-U.S. Gov't, Validation Studies",
author = "Daniela B{\"o}rnigen and L{\'e}on-Charles Tranchevent and Francisco Bonachela-Capdevila and Koenraad Devriendt and {De Moor}, Bart and {De Causmaecker}, Patrick and Yves Moreau",
year = "2012",
month = dec,
day = "1",
doi = "10.1093/bioinformatics/bts581",
language = "English",
volume = "28",
pages = "3081--3088",
journal = "BIOINFORMATICS",
issn = "1367-4803",
publisher = "Oxford University Press",
number = "23",

}

RIS

TY - JOUR

T1 - An unbiased evaluation of gene prioritization tools

AU - Börnigen, Daniela

AU - Tranchevent, Léon-Charles

AU - Bonachela-Capdevila, Francisco

AU - Devriendt, Koenraad

AU - De Moor, Bart

AU - De Causmaecker, Patrick

AU - Moreau, Yves

PY - 2012/12/1

Y1 - 2012/12/1

N2 - MOTIVATION: Gene prioritization aims at identifying the most promising candidate genes among a large pool of candidates-so as to maximize the yield and biological relevance of further downstream validation experiments and functional studies. During the past few years, several gene prioritization tools have been defined, and some of them have been implemented and made available through freely available web tools. In this study, we aim at comparing the predictive performance of eight publicly available prioritization tools on novel data. We have performed an analysis in which 42 recently reported disease-gene associations from literature are used to benchmark these tools before the underlying databases are updated.RESULTS: Cross-validation on retrospective data provides performance estimate likely to be overoptimistic because some of the data sources are contaminated with knowledge from disease-gene association. Our approach mimics a novel discovery more closely and thus provides more realistic performance estimates. There are, however, marked differences, and tools that rely on more advanced data integration schemes appear more powerful.CONTACT: yves.moreau@esat.kuleuven.beSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

AB - MOTIVATION: Gene prioritization aims at identifying the most promising candidate genes among a large pool of candidates-so as to maximize the yield and biological relevance of further downstream validation experiments and functional studies. During the past few years, several gene prioritization tools have been defined, and some of them have been implemented and made available through freely available web tools. In this study, we aim at comparing the predictive performance of eight publicly available prioritization tools on novel data. We have performed an analysis in which 42 recently reported disease-gene associations from literature are used to benchmark these tools before the underlying databases are updated.RESULTS: Cross-validation on retrospective data provides performance estimate likely to be overoptimistic because some of the data sources are contaminated with knowledge from disease-gene association. Our approach mimics a novel discovery more closely and thus provides more realistic performance estimates. There are, however, marked differences, and tools that rely on more advanced data integration schemes appear more powerful.CONTACT: yves.moreau@esat.kuleuven.beSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

KW - Databases, Genetic

KW - Genetic Association Studies

KW - Humans

KW - Internet

KW - Comparative Study

KW - Journal Article

KW - Research Support, Non-U.S. Gov't

KW - Validation Studies

U2 - 10.1093/bioinformatics/bts581

DO - 10.1093/bioinformatics/bts581

M3 - SCORING: Journal article

C2 - 23047555

VL - 28

SP - 3081

EP - 3088

JO - BIOINFORMATICS

JF - BIOINFORMATICS

SN - 1367-4803

IS - 23

ER -