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
Niroula, Abhishek; Vihinen, Mauno (2017) PON-P and PON-P2 predictor performance in CAGI challenges: Lessons learned. Hum Mutat 38:1085-1091
Kreimer, Anat; Zeng, Haoyang; Edwards, Matthew D et al. (2017) Predicting gene expression in massively parallel reporter assays: A comparative study. Hum Mutat 38:1240-1250
Carraro, Marco; Minervini, Giovanni; Giollo, Manuel et al. (2017) Performance of in silico tools for the evaluation of p16INK4a (CDKN2A) variants in CAGI. Hum Mutat 38:1042-1050
Beer, Michael A (2017) Predicting enhancer activity and variant impact using gkm-SVM. Hum Mutat 38:1251-1258
Daneshjou, Roxana; Wang, Yanran; Bromberg, Yana et al. (2017) Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges. Hum Mutat 38:1182-1192
Cai, Binghuang; Li, Biao; Kiga, Nikki et al. (2017) Matching phenotypes to whole genomes: Lessons learned from four iterations of the personal genome project community challenges. Hum Mutat 38:1266-1276
Capriotti, Emidio; Martelli, Pier Luigi; Fariselli, Piero et al. (2017) Blind prediction of deleterious amino acid variations with SNPs&GO. Hum Mutat 38:1064-1071
Wang, Maggie Haitian; Chang, Billy; Sun, Rui et al. (2017) Stratified polygenic risk prediction model with application to CAGI bipolar disorder sequencing data. Hum Mutat 38:1235-1239
Giollo, Manuel; Jones, David T; Carraro, Marco et al. (2017) Crohn disease risk prediction-Best practices and pitfalls with exome data. Hum Mutat 38:1193-1200
Xu, Qifang; Tang, Qingling; Katsonis, Panagiotis et al. (2017) Benchmarking predictions of allostery in liver pyruvate kinase in CAGI4. Hum Mutat 38:1123-1131

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