Flexible and scalable diagnostic filtering of genomic variants using G2P with Ensembl VEP

Anja Thormann; Mihail Halachev; William McLaren; David J. Moore; Victoria Svinti; Archie Campbell; Shona M. Kerr; Marc Tischkowitz; Sarah E. Hunt; Malcolm G. Dunlop; Matthew E. Hurles; Caroline F. Wright; Helen V. Firth; Fiona Cunningham; David R. FitzPatrick

doi:10.1038/s41467-019-10016-3

Flexible and scalable diagnostic filtering of genomic variants using G2P with Ensembl VEP

Anja Thormann, Mihail Halachev, William McLaren, David J. Moore, Victoria Svinti, Archie Campbell, Shona M. Kerr, Marc Tischkowitz, Sarah E. Hunt, Malcolm G. Dunlop, Matthew E. Hurles, Caroline F. Wright, Helen V. Firth, Fiona Cunningham, David R. FitzPatrick

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Abstract

We aimed to develop an efficient, flexible and scalable approach to diagnostic genome-wide sequence analysis of genetically heterogeneous clinical presentations. Here we present G2P (www.ebi.ac.uk/gene2phenotype) as an online system to establish, curate and distribute datasets for diagnostic variant filtering via association of allelic requirement and mutational consequence at a defined locus with phenotypic terms, confidence level and evidence links. An extension to Ensembl Variant Effect Predictor (VEP), VEP-G2P was used to filter both disease-associated and control whole exome sequence (WES) with Developmental Disorders G2P (G2P^DD; 2044 entries). VEP-G2P^DD shows a sensitivity/precision of 97.3%/33% for de novo and 81.6%/22.7% for inherited pathogenic genotypes respectively. Many of the missing genotypes are likely false-positive pathogenic assignments. The expected number and discriminative features of background genotypes are defined using control WES. Using only human genetic data VEP-G2P performs well compared to other freely-available diagnostic systems and future phenotypic matching capabilities should further enhance performance.

Original language	English
Article number	2373
Number of pages	10
Journal	Nature Communications
Volume	10
Issue number	2373
DOIs	https://doi.org/10.1038/s41467-019-10016-3
Publication status	Published - 30 May 2019

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10.1038/s41467-019-10016-3Licence: Creative Commons: Attribution (CC-BY)

Flexible and Scalable Diagnostic Filtering of Genomic Variants using G2P with Ensembl VEPAccepted author manuscript, 72.9 KBLicence: Creative Commons: Attribution (CC-BY)
s41467-019-10016-3Final published version, 1.09 MBLicence: Creative Commons: Attribution (CC-BY)

Stratifying Resilience and Depression Longitudinally
McIntosh, A. (Principal Investigator), Deary, I. (Co-investigator), Evans, K. (Co-investigator), Haley, C. (Co-investigator) & Porteous, D. (Co-investigator)
UK-based charities
1/01/15 → 30/06/21
Project: Research

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Thormann, A., Halachev, M., McLaren, W., Moore, D. J., Svinti, V., Campbell, A., Kerr, S. M., Tischkowitz, M., Hunt, S. E., Dunlop, M. G., Hurles, M. E., Wright, C. F., Firth, H. V., Cunningham, F., & FitzPatrick, D. R. (2019). Flexible and scalable diagnostic filtering of genomic variants using G2P with Ensembl VEP. Nature Communications, 10(2373), Article 2373. https://doi.org/10.1038/s41467-019-10016-3

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title = "Flexible and scalable diagnostic filtering of genomic variants using G2P with Ensembl VEP",

abstract = "We aimed to develop an efficient, flexible and scalable approach to diagnostic genome-wide sequence analysis of genetically heterogeneous clinical presentations. Here we present G2P (www.ebi.ac.uk/gene2phenotype) as an online system to establish, curate and distribute datasets for diagnostic variant filtering via association of allelic requirement and mutational consequence at a defined locus with phenotypic terms, confidence level and evidence links. An extension to Ensembl Variant Effect Predictor (VEP), VEP-G2P was used to filter both disease-associated and control whole exome sequence (WES) with Developmental Disorders G2P (G2PDD; 2044 entries). VEP-G2PDD shows a sensitivity/precision of 97.3%/33% for de novo and 81.6%/22.7% for inherited pathogenic genotypes respectively. Many of the missing genotypes are likely false-positive pathogenic assignments. The expected number and discriminative features of background genotypes are defined using control WES. Using only human genetic data VEP-G2P performs well compared to other freely-available diagnostic systems and future phenotypic matching capabilities should further enhance performance.",

author = "Anja Thormann and Mihail Halachev and William McLaren and Moore, {David J.} and Victoria Svinti and Archie Campbell and Kerr, {Shona M.} and Marc Tischkowitz and Hunt, {Sarah E.} and Dunlop, {Malcolm G.} and Hurles, {Matthew E.} and Wright, {Caroline F.} and Firth, {Helen V.} and Fiona Cunningham and FitzPatrick, {David R.}",

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doi = "10.1038/s41467-019-10016-3",

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Thormann, A, Halachev, M, McLaren, W, Moore, DJ, Svinti, V, Campbell, A , Kerr, SM, Tischkowitz, M, Hunt, SE, Dunlop, MG, Hurles, ME, Wright, CF, Firth, HV, Cunningham, F & FitzPatrick, DR 2019, 'Flexible and scalable diagnostic filtering of genomic variants using G2P with Ensembl VEP', Nature Communications, vol. 10, no. 2373, 2373. https://doi.org/10.1038/s41467-019-10016-3

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T1 - Flexible and scalable diagnostic filtering of genomic variants using G2P with Ensembl VEP

AU - Thormann, Anja

AU - Halachev, Mihail

AU - McLaren, William

AU - Moore, David J.

AU - Svinti, Victoria

AU - Campbell, Archie

AU - Kerr, Shona M.

AU - Tischkowitz, Marc

AU - Hunt, Sarah E.

AU - Dunlop, Malcolm G.

AU - Hurles, Matthew E.

AU - Wright, Caroline F.

AU - Firth, Helen V.

AU - Cunningham, Fiona

AU - FitzPatrick, David R.

PY - 2019/5/30

Y1 - 2019/5/30

N2 - We aimed to develop an efficient, flexible and scalable approach to diagnostic genome-wide sequence analysis of genetically heterogeneous clinical presentations. Here we present G2P (www.ebi.ac.uk/gene2phenotype) as an online system to establish, curate and distribute datasets for diagnostic variant filtering via association of allelic requirement and mutational consequence at a defined locus with phenotypic terms, confidence level and evidence links. An extension to Ensembl Variant Effect Predictor (VEP), VEP-G2P was used to filter both disease-associated and control whole exome sequence (WES) with Developmental Disorders G2P (G2PDD; 2044 entries). VEP-G2PDD shows a sensitivity/precision of 97.3%/33% for de novo and 81.6%/22.7% for inherited pathogenic genotypes respectively. Many of the missing genotypes are likely false-positive pathogenic assignments. The expected number and discriminative features of background genotypes are defined using control WES. Using only human genetic data VEP-G2P performs well compared to other freely-available diagnostic systems and future phenotypic matching capabilities should further enhance performance.

AB - We aimed to develop an efficient, flexible and scalable approach to diagnostic genome-wide sequence analysis of genetically heterogeneous clinical presentations. Here we present G2P (www.ebi.ac.uk/gene2phenotype) as an online system to establish, curate and distribute datasets for diagnostic variant filtering via association of allelic requirement and mutational consequence at a defined locus with phenotypic terms, confidence level and evidence links. An extension to Ensembl Variant Effect Predictor (VEP), VEP-G2P was used to filter both disease-associated and control whole exome sequence (WES) with Developmental Disorders G2P (G2PDD; 2044 entries). VEP-G2PDD shows a sensitivity/precision of 97.3%/33% for de novo and 81.6%/22.7% for inherited pathogenic genotypes respectively. Many of the missing genotypes are likely false-positive pathogenic assignments. The expected number and discriminative features of background genotypes are defined using control WES. Using only human genetic data VEP-G2P performs well compared to other freely-available diagnostic systems and future phenotypic matching capabilities should further enhance performance.

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VL - 10

JO - Nature Communications

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M1 - 2373

ER -

Flexible and scalable diagnostic filtering of genomic variants using G2P with Ensembl VEP

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Stratifying Resilience and Depression Longitudinally

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