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Lessons from the CAGI-4 Hopkins clinical panel challenge

Chandonia, J-M; Adhikari, A; Carraro, M; Chhibber, A; Cutting, GR; Fu, Y; Gasparini, A; ... Buckley, BA; + view all (2017) Lessons from the CAGI-4 Hopkins clinical panel challenge. Human Mutation , 38 (9) pp. 1155-1168. 10.1002/humu.23225. Green open access

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Abstract

The CAGI-4 Hopkins clinical panel challenge was an attempt to assess state of the art methods for clinical phenotype prediction from DNA sequence. Participants were provided with exonic sequences of 83 genes for 106 patients from the Johns Hopkins DNA Diagnostic Laboratory. Five groups participated in the challenge, predicting both the probability that each patient had each of fourteen possible classes of disease, as well as one or more causal variants. In cases where the Hopkins laboratory reported a variant, at least one predictor correctly identified the disease class in 36 of 43 patients (84%). Even in cases where the Hopkins laboratory did not find a variant, at least one predictor correctly identified the class in 39 of 63 patients (62%). Each prediction group correctly diagnosed at least one patient that was not successfully diagnosed by any other groups. We discuss the causal variant predictions by the different groups and their implications for further development of methods to assess variants of unknown significance. Our results suggest that clinically relevant variants may be missed when physicians order small panels targeted on a specific phenotype. We also quantify the false positive rate of DNA-guided analysis in the absence of prior phenotypic indication. This article is protected by copyright. All rights reserved.

Type: Article
Title: Lessons from the CAGI-4 Hopkins clinical panel challenge
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/humu.23225
Publisher version: http://doi.org/10.1002/humu.23225
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: CAGI, genetic testing, phenotype prediction, variant interpretation
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1551522
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