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Genetic association analysis with R: latest developments

Published on January 28, 2026   23 min

A selection of talks on Genetics & Epigenetics

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0:00
Hello, welcome. Today, I'm going to revisit genetic association analysis with R, a topic I first covered back in 2009.
0:13
I'm excited to share with you several topics. The first R is in relation to the Linux environment and software, including installation Integrated Development Environment, IDE, and some language elements. Second, applications that range from the association models, including generalized linear mixed models and artificial intelligence, AI, as well as annotation using tools such as biomaRt and other tools such as a graphic user interface, GUI, and Shiny. Third, package development and distribution via GitHub. Last, but not least, web distribution.
0:57
What has changed since our early review in 2009? In data handling, dplyr is now widely used, and omics data involves customized DNA, gene expression, RNA-Seq, proteome, and single-cell data. In a modeling framework that includes a generic facility in data science and AI. In graphics notably the ggplot2 package with a version change from 0.8.5 to 3.5.1. In performance, which integrates with computer systems and major program languages such as C, C++, and others. In the package, which reaches over 22,000 at the official website excluding Bioconductor and GitHub. Last, I'm able to showcase with you the gap that involved several packages and a new package called pQTLtools.

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Genetic association analysis with R: latest developments

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