Hello,
My current project is examining variation in cold tolerance and cold-induced changes in gene expression across isogenic fly lines. The basics of the project is that I phenotyped 14 isogenic lineages. The 14 lineages fell out into 3 categories: high, average, and low. From there I selected two lineages from the high and two lineages from the low categories. Individuals from these lineages were then subjected to two treatments: 1) exposed or 2) non-exposed (control). What I am now trying to do is examine differential gene expression across the categories (high vs. low), across treatments (control vs. exposed), and the interaction between category and treatment. I've provided a breakdown of my fixed and random effects below.
Fixed Effects: Categories (x2: High and Low) Treatment (x2: Control and Exposed) Category x Treatment interaction
Random Effect Lineages (x4: 2 nested within High category, 2 nested within Low category)
The issue I am having is that I need to include line, nested within category as a random effect to account for the variation between lineages within categories. I have been using the r package LIMMA to do this as it can support random effects unlike DESeq2. I've gone through the LIMMA User Guide and have been able to get everything working properly, except for the inclusion of my nested, random effect. Unfortunately, I don't know how to do that or if it is even possible.
Has anyone come across this issue before? Any help would be greatly appreciated! I can provide more information upon request.
Best,
-Mark
What are the nested random effects? It looks like you only have one random effect (lineage) in your design.
Hi Ryan,
The lineages are not dispersed evenly across both categories. Lineage is nested within category, with 2 lineages in the High category and 2 lineages in the Low category.
Best,
-Mark