Gene Ontology: Pitfalls, Biases, and Remedies.

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Ressource 1Download: 978-1-4939-3743-1_14 (1).pdf (436.87 [Ko])
State: Public
Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_CBFCF5FD756A
Type
A part of a book
Publication sub-type
Chapter: chapter ou part
Collection
Publications
Institution
Title
Gene Ontology: Pitfalls, Biases, and Remedies.
Title of the book
Methods in molecular biology
Author(s)
Gaudet P., Dessimoz C.
Publisher
Springer
ISSN
1940-6029 (Electronic)
ISSN-L
1064-3745
Publication state
Published
Issued date
2017
Peer-reviewed
Oui
Volume
1446
Chapter
14
Pages
189-205
Language
english
Abstract
The Gene Ontology (GO) is a formidable resource, but there are several considerations about it that are essential to understand the data and interpret it correctly. The GO is sufficiently simple that it can be used without deep understanding of its structure or how it is developed, which is both a strength and a weakness. In this chapter, we discuss some common misinterpretations of the ontology and the annotations. A better understanding of the pitfalls and the biases in the GO should help users make the most of this very rich resource. We also review some of the misconceptions and misleading assumptions commonly made about GO, including the effect of data incompleteness, the importance of annotation qualifiers, and the transitivity or lack thereof associated with different ontology relations. We also discuss several biases that can confound aggregate analyses such as gene enrichment analyses. For each of these pitfalls and biases, we suggest remedies and best practices.
Keywords
Animals, Data Mining/methods, Databases, Genetic, Gene Ontology, Humans, Molecular Sequence Annotation/methods, Proteins/genetics, Species Specificity, Bias, Confounding, Data mining, Gene ontology, Gene/protein annotation, Simpson’s paradox
Pubmed
Create date
30/11/2016 22:38
Last modification date
30/07/2024 7:02
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