We propose to organize two further Critical Assessment of Genome Interpretation (CAGI) meetings, in December 2012 and December 2013. As in 2010 and 2011, the meetings 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 due to the burgeoning availability of individuals'genomes, and the desire to interpret these for research and clinical applications. Currently, the field lacks a consensus on the absolute and relative suitability of th panoply of different methods for prediction. These meetings will provide the first large-scale assessment of the state of the art of genome variation interpretation. The outcome of the meetings will be published to ensure wide dissemination of results. In the CAGI experiments, modeled on the Critical Assessment of Structure Prediction (CASP), participants are provided genetic variants and 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 genomes and exomes, nsSNPs, splice-affecting SNPs, and copy number variation along with other data such as transcriptomics. Independent assessors will evaluate the predictions against experimentally characterized phenotypes. A CAGI Conference is held at the end of each 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 a broader audience via publication of results in peer-reviewed journals. The new CAGI experiments will continue the process started with the CAGI pilot in 2010, and the first full-scale CAGI experiment in 2011. The 2011 experiment yielded a total of 117 predictions on 11 datasets, from 21 groups from 18 countries. 55 people attended the December 2011 meeting, and we are disseminating results via open access publications and conference presentations. The participating community was overwhelmingly of the opinion that this experiment is necessary and should be organized again on an ongoing basis. The organizers will strongly encourage the participation of women and underrepresented 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 registration and approximately 2/3 of their other meeting participation costs (travel and subsistence). In addition, we seek funding to subsidize registration and approximately half of meeting participation costs of the independent assessors, some data providers and scientific council members, and the organizers of the CAGI experiments.

Public Health Relevance

Genomic variation is responsible for numerous rare diseases, propensity for many common traits and diseases, drug response, 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 in understanding genomic variation.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Conference (R13)
Project #
2R13HG006650-02
Application #
8459354
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Struewing, Jeffery P
Project Start
2011-09-01
Project End
2014-05-31
Budget Start
2012-09-01
Budget End
2013-05-31
Support Year
2
Fiscal Year
2012
Total Cost
$25,000
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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