We propose to organize a meeting titled Critical Assessment of Genome Interpretation (CAGI) in December 2011. The meeting will be the culmination of a community experiment to objectively assess computational methods for predicting the phenotypic impacts of genomic variation. The CAGI experiment is timely and of wide relevance because of the burgeoning availability of individuals'genomes, and the desire to interpret them for research and clinical applications. Currently, the field lacks a consensus on the absolute and relative suitability of the panoply of different methods for prediction. This meeting will provide the first large-scale assessment of the state of the art of genome variation interpretation, and outcome of the meeting will be published to ensure wide dissemination of the results. In the CAGI experiment, modeled on the Critical Assessment of Structure Prediction (CASP), participants are provided genetic variants and will make predictions of resulting molecular, cellular, or organismal phenotype. Datasets are expected to include rare disease, common traits and diseases, germline and somatic cancer variation, with a focus on nsSNPs, splice-affecting SNPs, exomes, and copy number variation. Independent assessors will evaluate the predictions against experimentally characterized phenotypes. The CAGI Conference is held at the end of the experiment. The specific goals of the meeting are: (1) to assess the quality of current computational methods for interpreting genomic data, and highlight innovations &progress;(2) to guide future research efforts in computational genome interpretation and build a strong community for collaboration and interaction;and (3) to disseminate results both amongst key members of the variant-phenotype prediction community at the meeting and to broader audience via publication of results in peer-reviewed journals. This will be the first full-scale CAGI experiment. In fall 2010 we organized the preliminary CAGI experiment, which yielded 108 predictions on 6 datasets, from 17 groups in 8 countries. Forty people attended the December 2010 workshop and seven viewed the live feed of the meeting. The community was unanimous that this experiment is necessary and should be organized again on a larger scale. The organizers will strongly encourage the participation of women and minorities, and broad participation of trainees and senior scientists at the CAGI meeting. Funding is requested for awarding 19 trainee fellowships for students and postdoctoral researchers to cover approximately 2/3 of their meeting participation costs (travel, registration, and subsistence). In addition, we seek funding to subsidize half of meeting participation costs of independent assessors and organizers of the CAGI experiment.

Public Health Relevance

Genomic variation is responsible for numerous rare diseases, propensity for many common traits and diseases, and is a key characteristic of cancer evolution. At present, our ability to characterize genetic differences far exceeds our capacity to interpret it either for basic research understanding or for clinical diagnosis. The Critical Assessment of Genome Interpretation will provide an evaluation of the current state-of- the-art and help promote progress to understand genomic variation.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Conference (R13)
Project #
1R13HG006650-01
Application #
8257337
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Struewing, Jeffery P
Project Start
2011-09-01
Project End
2012-08-31
Budget Start
2011-09-01
Budget End
2012-08-31
Support Year
1
Fiscal Year
2011
Total Cost
$24,735
Indirect Cost
Name
University of California Berkeley
Department
Other Basic Sciences
Type
Schools of Earth Sciences/Natur
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94704
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Hoskins, Roger A; Repo, Susanna; Barsky, Daniel et al. (2017) Reports from CAGI: The Critical Assessment of Genome Interpretation. Hum Mutat 38:1039-1041
Katsonis, Panagiotis; Lichtarge, Olivier (2017) Objective assessment of the evolutionary action equation for the fitness effect of missense mutations across CAGI-blinded contests. Hum Mutat 38:1072-1084
Laksshman, Sundaram; Bhat, Rajendra Rana; Viswanath, Vivek et al. (2017) DeepBipolar: Identifying genomic mutations for bipolar disorder via deep learning. Hum Mutat 38:1217-1224
Yin, Yizhou; Kundu, Kunal; Pal, Lipika R et al. (2017) Ensemble variant interpretation methods to predict enzyme activity and assign pathogenicity in the CAGI4 NAGLU (Human N-acetyl-glucosaminidase) and UBE2I (Human SUMO-ligase) challenges. Hum Mutat 38:1109-1122
Kundu, Kunal; Pal, Lipika R; Yin, Yizhou et al. (2017) Determination of disease phenotypes and pathogenic variants from exome sequence data in the CAGI 4 gene panel challenge. Hum Mutat 38:1201-1216
Pal, Lipika R; Kundu, Kunal; Yin, Yizhou et al. (2017) CAGI4 Crohn's exome challenge: Marker SNP versus exome variant models for assigning risk of Crohn disease. Hum Mutat 38:1225-1234
Pal, Lipika R; Kundu, Kunal; Yin, Yizhou et al. (2017) CAGI4 SickKids clinical genomes challenge: A pipeline for identifying pathogenic variants. Hum Mutat 38:1169-1181
Pejaver, Vikas; Mooney, Sean D; Radivojac, Predrag (2017) Missense variant pathogenicity predictors generalize well across a range of function-specific prediction challenges. Hum Mutat 38:1092-1108
Chandonia, John-Marc; Adhikari, Aashish; Carraro, Marco et al. (2017) Lessons from the CAGI-4 Hopkins clinical panel challenge. Hum Mutat 38:1155-1168

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