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FlashPCA: fast sparse canonical correlation analysis of genomic data

View ORCID ProfileGad Abraham, Michael Inouye
doi: https://doi.org/10.1101/047217
Gad Abraham
1Centre for Systems Genomics, School of BioSciences, University of Melbourne, Parkville 3010, VIC, Australia.
2Department of Pathology, Faculty of Medicine, Dentistry, and Health Sciences, University of Melbourne, Parkville 3010, VIC, Australia.
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Michael Inouye
1Centre for Systems Genomics, School of BioSciences, University of Melbourne, Parkville 3010, VIC, Australia.
2Department of Pathology, Faculty of Medicine, Dentistry, and Health Sciences, University of Melbourne, Parkville 3010, VIC, Australia.
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Abstract

Summary Sparse canonical correlation analysis (SCCA) is a useful approach for correlating one set of measurements, such as single nucleotide polymorphisms (SNPs), with another set of measurements, such as gene expression levels. We present a fast implementation of SCCA, enabling rapid analysis of hundreds of thousands of SNPs together with thousands of phenotypes. Our approach is implemented both as an R package flashpcaR and within the standalone commandline tool flashpca.

Availability and implementation https://github.com/gabraham/flashpca

Contact gad.abraham{at}unimelb.edu.au

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted April 06, 2016.
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FlashPCA: fast sparse canonical correlation analysis of genomic data
Gad Abraham, Michael Inouye
bioRxiv 047217; doi: https://doi.org/10.1101/047217
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FlashPCA: fast sparse canonical correlation analysis of genomic data
Gad Abraham, Michael Inouye
bioRxiv 047217; doi: https://doi.org/10.1101/047217

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