bioRxivGeneticsPreprint
Fitting penalized regressions on very large genetic data using snpnet and bigstatsr
Florian PrivéiD, Bjarni Jóhann VilhjálmssoniD, Hugues AschardiD
Abstract
Both R packages snpnet and bigstatsr allow for fitting penalized regressions on individual-level genetic data as large as the UK Biobank. Here we benchmark bigstatsr against snpnet for fitting penalized regressions on large genetic data. We find bigstatsr to be an order of magnitude faster than snpnet when applied to the UK Biobank data (from 4.5x to 35x). We also discuss the similarities and differences between the two packages, provide theoretical insights, and make recommendations on how to fit penalized regressions in the context of genetic data.
- assay: GWAS summary statistics
- research focus: benchmarking
- approach: statistical model
- approach: benchmark study
- Citations
- 3
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