Please excuse me for asking what I guess are elemental questions but I’m new to this kind of analyses. Anyway, here it goes:
1.) I would like to run a unifrac significance test with unifrac distance. I have replicate data in 6 groups (3 replicates /group). I know I can incorporate replicates using a design file but if I want to use the unifrac distance I would need to do the following I guess:
unifrac.weighted(tree=muscle.pick.good.filter.pick.subsample.phylip.tre, group=seqs.pick.good.pick.subsample.groups, random=T, name=muscle.pick.good.pick.subsample.names, distance=lt, processors=4)
unifrac.weighted(tree=muscle.pick.good.filter.pick.subsample.phylip.tre1.weighted.phylip.tre, group=design.design, groups=all, random=T)
Is this correct or should I do it some other way?
2.) What is the rationale between running and unweighted unifrac test on a tree constructed with Yue & Clayton distances like in the 454 SOP? As I have understood, the ThetaYC accounts for OTU abundance and the unweighted.unifrac does not, but i might be wrong.
3.) I have seen some different opinions regarding wheather rarefation should be performed or not. In the mothur tutorials I see it being implemented. Is this still advisble from your point of view? I lose quite a lot of samples this way and Im working with Sanger data (~300 sequences).
Your advice would be greatly appreciated.
Thanks in advance