I have a time course small RNA data from an infection of a pathogen in a plant. The aim is to see how the small RNA produced by both is linked to the responses of both to the infection.

What I was thinking was to combine the raw data and perform mirdeep2 to identify the small RNA reference set to count against although not sure if this will affect the output rather than identifying individual time points and combine the reference set. Then count using the quantifier script from mirdeep2. I'm using no known small RNA for the fungal part as can't find any but I am using the host and related small RNA for the plant found on the mirbase website.

I'm not sure whether to try mirdeep-p for the plant side yet which maybe is preferable as they say they have improved it for plants or just stick with mirdeep2?

It would be great if anyone could comment on whether the above plans sound reasonable or if there are limitations to it and if you think other methods would give a better result. I tried out the UEA software package but got some errors so haven't pursued it further. Once we get a counts table we will most likely pass it on to the stats people and the biologist can blast to identify the targets of those deferentially expressed.

Any suggestions welcome, not handled this type of data before.