Genome-wide association studies have produced a wealth of new genetic associations to numerous traits over the last few years. As such, new studies of these phenotypes often attempt to replicate previous associations in their samples, or examine how the effects of these SNPs are altered by environmental factors or clinical subtypes. This growing trend means that the results section must become multi-dimensional, accounting for all the ways by which samples were partitioned for analysis.
A great way to display regression coefficients is with forest plots, and an excellent example can be seen in the previous post.
There are various ways to produce these useful plots, but our colleague Sarah Pendergrass recently published a very nice tool for creating high-dimensional forest plots, like the one seen below.
This tool, called Synthesis-View provides several additional plot types that make the results of complex analyses much more accessible. You can read about the details here.
While Sarah designed this for the examination of multi-ethnic cohort studies, it could easily be adapted to simultaneously plot coefficients stratified by sex, age groups, or clinical subtypes.