Abstract
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. © The Author(s) 2012. Published by Oxford University Press.
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CITATION STYLE
Huang, H., Tata, S., & Prill, R. J. (2013). BlueSNP: R package for highly scalable genome-wide association studies using Hadoop clusters. Bioinformatics, 29(1), 135–136. https://doi.org/10.1093/bioinformatics/bts647
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