title: Lessons from the CAGI-4 Hopkins clinical panel challenge.
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 the 14 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 the 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 the 63 patients (62%). Each prediction group correctly diagnosed at least one patient that was not successfully diagnosed by any other group. We discuss the causal variant predictions by 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.
authors.affiliation: Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California.
authors.forename: John-Marc
authors.identifier: 0000-0002-5153-9079
authors.initials: JM
authors.lastname: Chandonia
authors.affiliation: Department of Plant and Microbial Biology, University of California, Berkeley, California.
authors.forename: Aashish
authors.initials: A
authors.lastname: Adhikari
authors.affiliation: Department of Biomedical Sciences, University of Padova, Padova, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Carraro
authors.affiliation: Roche Sequencing Solutions, Belmont, California.
authors.forename: Aparna
authors.initials: A
authors.lastname: Chhibber
authors.affiliation: McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
authors.forename: Garry R
authors.initials: GR
authors.lastname: Cutting
authors.affiliation: Roche Sequencing Solutions, Belmont, California.
authors.forename: Yao
authors.initials: Y
authors.lastname: Fu
authors.affiliation: Department of Biomedical Sciences, University of Padova, Padova, Italy.|Department of Women's and Children's Health, University of Padova, Padova, Italy.
authors.forename: Alessandra
authors.initials: A
authors.lastname: Gasparini
authors.affiliation: Department of Computer Science, University College London, London, United Kingdom.
authors.forename: David T
authors.initials: DT
authors.lastname: Jones
authors.affiliation: Qiagen Bioinformatics, Redwood City, California.
authors.forename: Andreas
authors.initials: A
authors.lastname: Kramer
authors.affiliation: Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland.|Computational Biology, Bioinformatics and Genomics, Biological Sciences Graduate Program, University of Maryland, College Park, Maryland.
authors.forename: Kunal
authors.initials: K
authors.lastname: Kundu
authors.affiliation: Roche Sequencing Solutions, Belmont, California.
authors.forename: Hugo Y K
authors.initials: HYK
authors.lastname: Lam
authors.affiliation: Department of Women's and Children's Health, University of Padova, Padova, Italy.
authors.forename: Emanuela
authors.initials: E
authors.lastname: Leonardi
authors.affiliation: Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland.|Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland.
authors.forename: John
authors.identifier: 0000-0002-3012-2282
authors.initials: J
authors.lastname: Moult
authors.affiliation: Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland.
authors.forename: Lipika R
authors.initials: LR
authors.lastname: Pal
authors.affiliation: Independent Consultant, Philadelphia, Pennsylvania.
authors.forename: David B
authors.initials: DB
authors.lastname: Searls
authors.affiliation: Qiagen Bioinformatics, Redwood City, California.
authors.forename: Sohela
authors.initials: S
authors.lastname: Shah
authors.affiliation: Division of Genetics, Department of Medicine, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts.|Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts.
authors.forename: Shamil
authors.initials: S
authors.lastname: Sunyaev
authors.affiliation: Department of Biomedical Sciences, University of Padova, Padova, Italy.|CNR Institute of Neuroscience, Padova, Italy.
authors.forename: Silvio C E
authors.identifier: 0000-0003-4525-7793
authors.initials: SCE
authors.lastname: Tosatto
authors.affiliation: Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland.|Computational Biology, Bioinformatics and Genomics, Biological Sciences Graduate Program, University of Maryland, College Park, Maryland.
authors.forename: Yizhou
authors.initials: Y
authors.lastname: Yin
authors.affiliation: McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
authors.forename: Bethany A
authors.initials: BA
authors.lastname: Buckley
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D020022:Genetic Predisposition to Disease; D005820:Genetic Testing; D006801:Humans; D010641:Phenotype; D017422:Sequence Analysis, DNA / Q000379:methods*
keywords: CAGI; genetic testing; phenotype prediction; variant interpretation