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A Fast and Flexible Algorithm for Solving the Lasso in Large-scale and Ultrahigh-dimensional Problems

Junyang Qian, Wenfei Du, View ORCID ProfileYosuke Tanigawa, Matthew Aguirre, Robert Tibshirani, Manuel A. Rivas, Trevor Hastie
doi: https://doi.org/10.1101/630079
Junyang Qian
1Department of Statistics, Stanford University
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Wenfei Du
1Department of Statistics, Stanford University
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Yosuke Tanigawa
2Department of Biomedical Data Science, Stanford University
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Matthew Aguirre
2Department of Biomedical Data Science, Stanford University
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Robert Tibshirani
1Department of Statistics, Stanford University
2Department of Biomedical Data Science, Stanford University
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Manuel A. Rivas
2Department of Biomedical Data Science, Stanford University
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Trevor Hastie
1Department of Statistics, Stanford University
2Department of Biomedical Data Science, Stanford University
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  • For correspondence: hastie@stanford.edu
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Abstract

Since its first proposal in statistics (Tibshirani, 1996), the lasso has been an effective method for simultaneous variable selection and estimation. A number of packages have been developed to solve the lasso efficiently. However as large datasets become more prevalent, many algorithms are constrained by efficiency or memory bounds. In this paper, we propose a meta algorithm batch screening iterative lasso (BASIL) that can take advantage of any existing lasso solver and build a scalable lasso solution for large datasets. We also introduce snpnet, an R package that implements the proposed algorithm on top of glmnet (Friedman et al., 2010a) for large-scale single nucleotide polymorphism (SNP) datasets that are widely studied in genetics. We demonstrate results on a large genotype-phenotype dataset from the UK Biobank, where we achieve state-of-the-art heritability estimation on quantitative and qualitative traits including height, body mass index, asthma and high cholesterol.

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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 May 07, 2019.
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A Fast and Flexible Algorithm for Solving the Lasso in Large-scale and Ultrahigh-dimensional Problems
Junyang Qian, Wenfei Du, Yosuke Tanigawa, Matthew Aguirre, Robert Tibshirani, Manuel A. Rivas, Trevor Hastie
bioRxiv 630079; doi: https://doi.org/10.1101/630079
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A Fast and Flexible Algorithm for Solving the Lasso in Large-scale and Ultrahigh-dimensional Problems
Junyang Qian, Wenfei Du, Yosuke Tanigawa, Matthew Aguirre, Robert Tibshirani, Manuel A. Rivas, Trevor Hastie
bioRxiv 630079; doi: https://doi.org/10.1101/630079

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