Genomic variant benchmark: if you cannot measure it, you cannot improve it.

Détails

Ressource 1Télécharger: 37798733_BIB_BFFAA42506DB.pdf (1750.84 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_BFFAA42506DB
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Genomic variant benchmark: if you cannot measure it, you cannot improve it.
Périodique
Genome biology
Auteur⸱e⸱s
Majidian S., Agustinho D.P., Chin C.S., Sedlazeck F.J., Mahmoud M.
ISSN
1474-760X (Electronic)
ISSN-L
1474-7596
Statut éditorial
Publié
Date de publication
05/10/2023
Peer-reviewed
Oui
Volume
24
Numéro
1
Pages
221
Langue
anglais
Notes
Publication types: Journal Article ; Review
Publication Status: epublish
Résumé
Genomic benchmark datasets are essential to driving the field of genomics and bioinformatics. They provide a snapshot of the performances of sequencing technologies and analytical methods and highlight future challenges. However, they depend on sequencing technology, reference genome, and available benchmarking methods. Thus, creating a genomic benchmark dataset is laborious and highly challenging, often involving multiple sequencing technologies, different variant calling tools, and laborious manual curation. In this review, we discuss the available benchmark datasets and their utility. Additionally, we focus on the most recent benchmark of genes with medical relevance and challenging genomic complexity.
Mots-clé
Benchmark datasets, Genetic variation, Indels, Medical genes, SNPs, Sequencing technology, Structural variant
Pubmed
Open Access
Oui
Création de la notice
09/10/2023 12:36
Dernière modification de la notice
25/01/2024 7:43
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