Josep’s research focuses on the development of tools to better understand complex diseases using all types of genetic and genomic data. Particularly, he has been working on the development of several strategies to enhance the meaningful biological information obtained from genome-wide association studies (GWAS). To attempt this goal, Josep and his team are developing several approaches in parallel, and have particularly focused on type 2 diabetes (Mercader et. al. PLoS Genet. 2012 Dec;8(12)). These methods can be summarized along these lines:
1- Development of novel strategies for pathway analyses using GWAS data. For this, the team is developing new statistical methods to score the global genetic liability of each gene, as well as adapting pathway analyses successfully applied for gene expression data analysis that take into account the topology of the network.
2- Development of enhanced methods for genotype imputation, in order to better fine-map disease genes and to identify novel associated loci, using existing raw GWAS data. For this, the team uses the latest reference panels, including the 1000 Genomes reference panels, and have adapted this methodology for efficiently using the supercomputing resources available at BSC.
3- Improvement of epistasis analysis, (i. e. genetic interaction analysis) using GWAS datasets and guided by the existing biological knowledge to reduce the search space and to provide a better interpretation of the identified interactions.
Being part of Dr. Jose Florez and Dr. David Altshuler’s lab at the Broad Institute and the Massachusetts General Hospital, is a great opportunity to validate some of the findings provided by all these computational methods. Additionally, during his stay at Dr. Altshuler and Dr. Florez labs, Josep Is having the opportunity to explore the contribution of genetic variation in T2D in Mexican and Latinos population, where many population specific variants may contribute to the disease.