Using Edge R GLM fit, I have noted a high BCV between samples across 2 time points and 3 treatments. The BCV lies at 0.9. The experiment made use of plants taken from the wild, and acclimatised for weeks. Physiology measurements suggested all plants had acclimatised the same and no significance was between treatments, suggesting they were all the same at the start of experiment at the physiology level.
As for differential expression, is it out of the question to conduct this sort of analysis with such a high BCV? I have looked around and people often report a BCV around 0.2-0.6. Trinity was used to assemble the ome, followed by RSEM. Just curious if it's worth trying to follow this work up. 3 replicates were used per treatment and time point (due to budget). In hindsight more reps = more statistical power.
Does anyone know of any papers were they have reported high BCVs?
Thanks for any input/ advice.
