title: BlueSNP: R package for highly scalable genome-wide association studies using Hadoop clusters.
abstract: CONCLUSIONS
  Computational workloads for genome-wide association studies (GWAS) are growing in scale and complexity outpacing the capabilities of single-threaded software designed for personal computers. The BlueSNP R package implements GWAS statistical tests in the R programming language and executes the calculations across computer clusters configured with Apache Hadoop, a de facto standard framework for distributed data processing using the MapReduce formalism. BlueSNP makes computationally intensive analyses, such as estimating empirical p-values via data permutation, and searching for expression quantitative trait loci over thousands of genes, feasible for large genotype-phenotype datasets.
  
  
  METHODS
  http://github.com/ibm-bioinformatics/bluesnp
authors.affiliation: Healthcare Informatics, IBM Almaden Research Center, San Jose, CA 95120, USA.
authors.forename: Hailiang
authors.initials: H
authors.lastname: Huang
authors.forename: Sandeep
authors.initials: S
authors.lastname: Tata
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Prill
mesh_terms: D055106:Genome-Wide Association Study; D006801:Humans; D010641:Phenotype; D040641:Quantitative Trait Loci; D012984:Software