eprintid: 10106670
rev_number: 16
eprint_status: archive
userid: 608
dir: disk0/10/10/66/70
datestamp: 2020-08-04 09:36:02
lastmod: 2021-09-21 22:09:06
status_changed: 2020-08-04 09:36:02
type: article
metadata_visibility: show
creators_name: Warwick Vesztrocy, A
creators_name: Dessimoz, C
title: Benchmarking gene ontology function predictions using negative annotations
ispublished: pub
divisions: UCL
divisions: B02
divisions: C08
divisions: D09
divisions: F99
note: This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/),
which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited
abstract: Motivation:
With the ever-increasing number and diversity of sequenced species, the challenge to characterize genes with functional information is even more important. In most species, this characterization almost entirely relies on automated electronic methods. As such, it is critical to benchmark the various methods. The Critical Assessment of protein Function Annotation algorithms (CAFA) series of community experiments provide the most comprehensive benchmark, with a time-delayed analysis leveraging newly curated experimentally supported annotations. However, the definition of a false positive in CAFA has not fully accounted for the open world assumption (OWA), leading to a systematic underestimation of precision. The main reason for this limitation is the relative paucity of negative experimental annotations.

Results:
This article introduces a new, OWA-compliant, benchmark based on a balanced test set of positive and negative annotations. The negative annotations are derived from expert-curated annotations of protein families on phylogenetic trees. This approach results in a large increase in the average information content of negative annotations. The benchmark has been tested using the naïve and BLAST baseline methods, as well as two orthology-based methods. This new benchmark could complement existing ones in future CAFA experiments.
date: 2020-07
date_type: published
official_url: https://doi.org/10.1093/bioinformatics/btaa466
oa_status: green
full_text_type: pub
pmcid: PMC7355306
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1799540
doi: 10.1093/bioinformatics/btaa466
pii: 5870480
lyricists_name: Dessimoz, Christophe
lyricists_id: CDESS31
actors_name: Flynn, Bernadette
actors_id: BFFLY94
actors_role: owner
full_text_status: public
publication: Bioinformatics
volume: 36
number: S1
pagerange: i210-i218
event_location: England
citation:        Warwick Vesztrocy, A;    Dessimoz, C;      (2020)    Benchmarking gene ontology function predictions using negative annotations.                   Bioinformatics , 36  (S1)   i210-i218.    10.1093/bioinformatics/btaa466 <https://doi.org/10.1093/bioinformatics%2Fbtaa466>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10106670/1/btaa466.pdf