PT  - JOURNAL ARTICLE
AU  - Oriol Canela-Xandri
AU  - Andy Law
AU  - Alan Gray
AU  - John A. Woolliams
AU  - Albert Tenesa
TI  - DISSECT: A new tool for analyzing extremely large genomic datasets
AID  - 10.1101/020453
DP  - 2015 Jan 01
TA  - bioRxiv
PG  - 020453
4099  - http://biorxiv.org/content/early/2015/06/05/020453.short
4100  - http://biorxiv.org/content/early/2015/06/05/020453.full
AB  - Computational tools are quickly becoming the main bottleneck to analyze large-scale genomic and genetic data. This big-data problem, affecting a wide range of fields, is becoming more acute with the fast increase of data available. To address it, we developed DISSECT, a new, easy to use, and freely available software able to exploit the parallel computer architectures of supercomputers to perform a wide range of genomic and epidemiologic analyses which currently can only be carried out on reduced sample sizes or in restricted conditions. We showcased our new tool by addressing the challenge of predicting phenotypes from genotype data in human populations using Mixed Linear Model analysis. We analyzed simulated traits from half a million individuals genotyped for 590,004 SNPs using the combined computational power of 8,400 processor cores. We found that prediction accuracies in excess of 80% of the theoretical maximum could be achieved with large numbers of training individuals.