Organizers of the Critical Assessment of Genome Interpretation experiment are still accepting submissions for some of the CAGI 2012 challenges.
The deadline for submissions for the remaining open challenges is March 28, 2013.
There are currently nine open challenges. In one, participants are provided with patients' exome data and asked to identify which individuals have Crohn's disease and which do not. A second challenge asks participants to predict the pathogenicity of rare variants in two proteins in the Mre11–Rad50–Nbs1, or MRN, complex; and a third calls for predictions about how mutations in p53 gene exons affect mRNA splicing.
In the fourth challenge, participants are expected to submit predictions that match genomes to clinical phenotypes using data from the Personal Genome Project; the fifth provides exome data from two families that have individuals with metabolic disorders and asks participants to identify associated mutations as well as which members of the families have abnormal lipid and cholesterol levels; while the sixth challenge calls for predictions about how well variants of the p16 tumor suppressor protein inhibit cell proliferation.
The seventh challenge calls for predictions about the impacts of microbial gene disruptions on cell growth under stress conditions; the eighth provides participants with whole genome data from a family affected by primary congenital glaucoma and asks them to predict the genetic basis of the disease; and the final challenge asks participants to identify the mechanisms that underlie genetic loci associated with the risk of seven complex trait diseases.
A tenth challenge in which participants were expected to predict which variants of the BRCA1 and BRCA2 genes are associated with increased risk for breast cancer closed last October.
The current CAGI experiment will culminate in a conference to be held in Berlin, Germany on July 17-18 prior to the start of this year's Intelligent Systems for Molecular Biology conference.
CAGI was launched in 2010 by researchers from the University of California, Berkeley and the University of Maryland in order to evaluate the effectiveness of computational methods used to make predictions about the impact of genomic variants on phenotypes (BI 11/12/2010).