Grow your data science skills at posit::conf(2024)

August 12th-14th in Seattle

For nearly 20 years, I’ve been developing, maintaining, and supporting an R package, R/qtl, for mapping quantitative trait loci (genetic loci that contribute to variation in quantitative traits, such as blood pressure) in experimental crosses (such as in mice). It’s a rather large package, with 39k lines of R code, 24k lines of C code, and nearly 300 user-accessible functions. In the past several years, I’ve been working on rewriting the package, to better handle high-dimensional data and more complex experimental crosses. This has been a good opportunity to take advantage of many new tools, including Rcpp, Roxygen2, and testthat. I’ll describe my efforts to avoid repeating the mistakes I made the first time around.

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