Genome Wide Association Studies (GWAS) were considered during the last
decades to deal with causal genetic variants involved in complex diseases.
Single Nucleotide Polymorphisms (SNPs) are the most common genetic markers used in GWAS. The GCAT-Genomes for Life Cohort Study of the Genomes of Catalonia Project is aimed to study the role of genomic and epigenomic factors in the development of cancer and chronic diseases in the Catalonian population. Currently 3303 blood samples have been genotyped by SNP-arrays methods. In this talk, I present the GCAT Project and statistical methods as multidimensional scaling, markov chain monte carlo (MCMC) algorithms and logistic regression models which are involved in GWAS. Multidimensional scaling is presented as method to detect individuals from other populations, MCMC algorithms to increase the number of SNPs in the dataset by genotype imputation and logistic regression models to detect genetic associations with the disease. All the analysis are made with R, PLINK, IMPUTE2 and SNPTEST softwares.