Guidelines for releasing a variant effect predictor

被引：2

作者：

Livesey, Benjamin J. ^{[1
]}

Badonyi, Mihaly ^{[1
]}

Dias, Mafalda ^{[2
]}

Frazer, Jonathan ^{[2
]}

Kumar, Sushant ^{[3
,14
]}

Lindorff-Larsen, Kresten ^{[4
]}

Mccandlish, David M.

Orenbuch, Rose ^{[5
]}

Shearer, Courtney A. ^{[5
]}

Muffley, Lara ^{[6
,7
]}

Foreman, Julia ^{[8
]}

Glazer, Andrew M. ^{[9
]}

Lehner, Ben ^{[10
,15
,16
]}

Marks, Debora S. ^{[5
,11
]}

Roth, Frederick P. ^{[12
]}

Rubin, Alan F. ^{[13
,17
]}

Starita, Lea M. ^{[6
,7
]}

Marsh, Joseph A. ^{[1
]}

机构：

[1] Univ Edinburgh, Inst Genet & Canc, MRC Human Genet Unit, Edinburgh, Scotland

[2] Barcelona Inst Sci & Technol, Ctr Genom Regulat CRG, Barcelona, Spain

[3] Univ Toronto, Dept Med Biophys, Toronto, ON, Canada

[4] Univ Copenhagen, Linderstrom Lang Ctr Prot Sci, Dept Biol, Copenhagen, Denmark

[5] Harvard Med Sch, Dept Syst Biol, Boston, MA USA

[6] Univ Washington, Dept Genome Sci, Seattle, WA USA

[7] Brotman Baty Inst Precis Med, Seattle, WA USA

[8] European Mol Biol Lab, European Bioinformat Inst, Wellcome Genome Campus, Hinxton, Cambridge, England

[9] Vanderbilt Univ, Med Ctr, Nashville, TN USA

[10] Wellcome Sanger Inst, Cambridge, England

[11] Broad Inst MIT & Harvard, Boston, MA USA

[12] Univ Pittsburgh, Sch Med, Dept Computat & Syst Biol, Pittsburgh, PA USA

[13] Walter & Eliza Hall Inst Med Res, Bioinformat Div, Parkville, Australia

[14] Univ Hlth Network, Princess Margaret Canc Ctr, Toronto, ON, Canada

[15] Univ Pompeu Fabra UPF, Barcelona, Spain

[16] Inst Catalana Recerca & Estudis Avancats ICREA, Barcelona, Spain

[17] Univ Melbourne, Dept Med Biol, Parkville, Australia

来源：

GENOME BIOLOGY | 2025年 / 26卷 / 01期

基金：

英国医学研究理事会;

关键词：

SEQUENCE VARIANTS; RECOMMENDATIONS; PATHOGENICITY; PROTEIN; CLASSIFICATION; PRINCIPLES; TOOLS;

D O I：

10.1186/s13059-025-03572-z

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

Computational methods for assessing the likely impacts of mutations, known as variant effect predictors (VEPs), are widely used in the assessment and interpretation of human genetic variation, as well as in other applications like protein engineering. Many different VEPs have been released, and there is tremendous variability in their underlying algorithms, outputs, and the ways in which the methodologies and predictions are shared. This leads to considerable difficulties for users trying to navigate the selection and application of VEPs. Here, to address these issues, we provide guidelines and recommendations for the release of novel VEPs.

引用

页数：13

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