I have a large RNA microarray dataset that I am planning to analyze, but am having difficulty deciding what statistical tests to perform or R packages to used based on the experimental design. The design is as follows:
There are 21 patients who have had tissue biopsies performed in two different locations (C or M) over three time points depending on the schedule they were assigned to. They all had initial biopsies in a specific location, then repeat biopsies were taken in a small area of the same location at two later time points to see how the tissues changed over time.
Schedule 1: 0h, 6h, 24h Schedule 2: 0h, 24h, 48h Schedule 3: 0h, 48h 72h
Patients 1-7 were assigned to schedule 1, Pts. 8-14 assigned to schedule 2, and Pts. 15-21 assigned to schedule 3.
My question is what statistical analysis would help me answer the following questions:
1) What patterns of gene expression changes are seen in tissue C over time with respect to time 0hr? - I want to find genes that may not be highly expressed until after time 0hr, genes that are high in time 0hr and go down over time, or genes that are low in time 0hr increase during the middle timepoints and fall back down by the last timepoint.
2) Same as question 1 but for tissue M
3) Which genes expression patterns over time are similar to both tissues or unique to each tissue?
I was planning to use MaSigPro, but I read in the original article that it makes an assumption that observations are independent and doesn't account for repeated measures. Are there any suggestions for what R packages or statistical tests will help with analyzing this dataset?