Interactive Graphics for High-Dimensional Genetic Data

The value of interactive graphics for making sense of high-dimensional data has long been appreciated but is still not in routine use. I will describe my efforts to develop interactive graphical tools for genetic data, using JavaScript and D3. (The tools are available as an R package: R/qtlcharts, http://kbroman.org/qtlcharts).

I will focus on an expression genetics experiment in the mouse, with gene expression microarray data on each of six tissues, plus high-density genotype data, in each of 500 mice. I argue that in research with such data, precise statistical inference is not so important as data visualization.