z-logo
open-access-imgOpen Access
An unbiased evaluation of gene prioritization tools
Author(s) -
Daniela Börnigen,
Léon-Charles Tranchevent,
Francisco Bonachela-Capdevila,
Koenraad Devriendt,
Bart De Moor,
Patrick De Causmaecker,
Yves Moreau
Publication year - 2012
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bts581
Subject(s) - computer science , prioritization , benchmark (surveying) , relevance (law) , data mining , data science , machine learning , geodesy , management science , political science , economics , geography , law
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom