Literature DB >> 31066479

A fully-automated event-based variant prioritizing solution to the CAGI5 intellectual disability gene panel challenge.

Jingqi Chen1,2,3.   

Abstract

Recent applications of gene panel sequencing analysis have significantly helped with identifying genetic causes for inherited diseases. However, large amounts of candidate variants remain a major challenge for prioritizing, often requiring arbitrary cutoffs in multiple steps. In addition, existing tools often prioritize a list of promising candidates that require much manual work to evaluate. To this end, we designed an automated, basically cutoff-free scoring scheme named Context and Hereditary Event based Scoring Scheme (CHESS), that scores all possible inheritance events in each gene, by taking into consideration phenotypes, genotypes, and how the manual prioritization works. We applied CHESS to the Critical Assessment of Genome Interpretation 5 intellectual disability panel challenge, to assign clinical phenotypes to patients based on gene panel sequencing data. Through this blind testing, CHESS proved to be a leading and useful tool for genetic diagnosis in a research setting. Further analyses showed that precise phenotype terms played an important role in variant prioritization and that multiple etiologies may exist for some patients. CHESS also successfully identified many of the causal, putative and contributing variants. In the postchallenge analysis, we showed that our best submission performed slightly better than the predictions made by a state-of-the-art tool. We believe that CHESS can provide aid to this and many other diagnostic scenarios.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  gene panel sequencing; genetic diagnosis; intellectual disability; variant prioritization

Mesh:

Year:  2019        PMID: 31066479      PMCID: PMC6744322          DOI: 10.1002/humu.23781

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  29 in total

Review 1.  Predicting the effects of amino acid substitutions on protein function.

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2.  Next-generation diagnostics: gene panel, exome, or whole genome?

Authors:  Yu Sun; Claudia A L Ruivenkamp; Mariëtte J V Hoffer; Terry Vrijenhoek; Marjolein Kriek; Christi J van Asperen; Johan T den Dunnen; Gijs W E Santen
Journal:  Hum Mutat       Date:  2015-04-17       Impact factor: 4.878

3.  Technology: The $1,000 genome.

Authors:  Erika Check Hayden
Journal:  Nature       Date:  2014-03-20       Impact factor: 49.962

Review 4.  Clinical Genetic Testing for Familial Hypercholesterolemia: JACC Scientific Expert Panel.

Authors:  Amy C Sturm; Joshua W Knowles; Samuel S Gidding; Zahid S Ahmad; Catherine D Ahmed; Christie M Ballantyne; Seth J Baum; Mafalda Bourbon; Alain Carrié; Marina Cuchel; Sarah D de Ferranti; Joep C Defesche; Tomas Freiberger; Ray E Hershberger; G Kees Hovingh; Lala Karayan; Johannes Jacob Pieter Kastelein; Iris Kindt; Stacey R Lane; Sarah E Leigh; MacRae F Linton; Pedro Mata; William A Neal; Børge G Nordestgaard; Raul D Santos; Mariko Harada-Shiba; Eric J Sijbrands; Nathan O Stitziel; Shizuya Yamashita; Katherine A Wilemon; David H Ledbetter; Daniel J Rader
Journal:  J Am Coll Cardiol       Date:  2018-08-07       Impact factor: 24.094

Review 5.  Epilepsy associated with autism and attention deficit hyperactivity disorder: is there a genetic link?

Authors:  Adriana Lo-Castro; Paolo Curatolo
Journal:  Brain Dev       Date:  2013-05-29       Impact factor: 1.961

6.  pROC: an open-source package for R and S+ to analyze and compare ROC curves.

Authors:  Xavier Robin; Natacha Turck; Alexandre Hainard; Natalia Tiberti; Frédérique Lisacek; Jean-Charles Sanchez; Markus Müller
Journal:  BMC Bioinformatics       Date:  2011-03-17       Impact factor: 3.307

7.  Improved exome prioritization of disease genes through cross-species phenotype comparison.

Authors:  Peter N Robinson; Sebastian Köhler; Anika Oellrich; Kai Wang; Christopher J Mungall; Suzanna E Lewis; Nicole Washington; Sebastian Bauer; Dominik Seelow; Peter Krawitz; Christian Gilissen; Melissa Haendel; Damian Smedley
Journal:  Genome Res       Date:  2013-10-25       Impact factor: 9.043

8.  Analysis of protein-coding genetic variation in 60,706 humans.

Authors:  Monkol Lek; Konrad J Karczewski; Eric V Minikel; Kaitlin E Samocha; Eric Banks; Timothy Fennell; Anne H O'Donnell-Luria; James S Ware; Andrew J Hill; Beryl B Cummings; Taru Tukiainen; Daniel P Birnbaum; Jack A Kosmicki; Laramie E Duncan; Karol Estrada; Fengmei Zhao; James Zou; Emma Pierce-Hoffman; Joanne Berghout; David N Cooper; Nicole Deflaux; Mark DePristo; Ron Do; Jason Flannick; Menachem Fromer; Laura Gauthier; Jackie Goldstein; Namrata Gupta; Daniel Howrigan; Adam Kiezun; Mitja I Kurki; Ami Levy Moonshine; Pradeep Natarajan; Lorena Orozco; Gina M Peloso; Ryan Poplin; Manuel A Rivas; Valentin Ruano-Rubio; Samuel A Rose; Douglas M Ruderfer; Khalid Shakir; Peter D Stenson; Christine Stevens; Brett P Thomas; Grace Tiao; Maria T Tusie-Luna; Ben Weisburd; Hong-Hee Won; Dongmei Yu; David M Altshuler; Diego Ardissino; Michael Boehnke; John Danesh; Stacey Donnelly; Roberto Elosua; Jose C Florez; Stacey B Gabriel; Gad Getz; Stephen J Glatt; Christina M Hultman; Sekar Kathiresan; Markku Laakso; Steven McCarroll; Mark I McCarthy; Dermot McGovern; Ruth McPherson; Benjamin M Neale; Aarno Palotie; Shaun M Purcell; Danish Saleheen; Jeremiah M Scharf; Pamela Sklar; Patrick F Sullivan; Jaakko Tuomilehto; Ming T Tsuang; Hugh C Watkins; James G Wilson; Mark J Daly; Daniel G MacArthur
Journal:  Nature       Date:  2016-08-18       Impact factor: 49.962

Review 9.  Population Based Testing for Primary Prevention: A Systematic Review.

Authors:  Ranjit Manchanda; Faiza Gaba
Journal:  Cancers (Basel)       Date:  2018-11-05       Impact factor: 6.639

10.  The Ensembl Variant Effect Predictor.

Authors:  William McLaren; Laurent Gil; Sarah E Hunt; Harpreet Singh Riat; Graham R S Ritchie; Anja Thormann; Paul Flicek; Fiona Cunningham
Journal:  Genome Biol       Date:  2016-06-06       Impact factor: 13.583

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