Giri Narasimhan, Changsong Bu, et al.
Journal of Computational Biology
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.
Giri Narasimhan, Changsong Bu, et al.
Journal of Computational Biology
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Molecular Biology and Evolution
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Biomicrofluidics
Matthias Reumann, Blake G. Fitch, et al.
EMBC 2009