**0**wrote:

I have a dataset like this:

`rep1_group1 rep1_group2 rep1_group3 rep2_group1 rep2_group2 rep2_group3 rep3_group1 rep3_group2 rep3_group3`

18.26426 18.50355 17.87981 18.14181 18.12318 18.37539 17.54155 17.62264 17.21371

21.10751 21.88614 21.26385 21.42588 21.42358 21.48596 21.18138 21.64957 21.56978

19.95816 19.93991 19.17141 19.23463 19.49048 19.69481 19.99466 20.27674 19.83937

15.77427 15.28338 15.56018 14.74557 15.12376 14.87215 17.58013 17.51229 17.24869

18.55157 18.75156 18.51595 18.69129 18.45551 18.9907 18.31092 18.28075 18.00218

24.40756 24.3009 24.0354 23.87117 24.03002 24.39447 24.45595 24.40041 24.03842

20.6223 20.62194 21.19045 20.85316 20.24748 20.99583 21.70248 20.83252 21.417

18.53522 18.20705 17.84586 18.45471 18.03112 18.24859 17.71512 17.46969 17.20132

17.87237 17.80663 15.99771 16.63991 17.51884 17.11533 18.12308 17.90783 18.29576

So simply descibing it rows contain measurements, and columns contain 3 study groups each in 3 replicates (rep1, rep2, rep3)

When I normally apply my transformations to the data to obtain pca:

`library(ape)`

library(data.table)

library(vegan)

tran <- t(data)

tran.pr.b <- vegdist(tran, "bray")

tran.pcoa.b <- pcoa(tran.pr.b)

plot(tran.pcoa.b$vectors[,1:2],main="pcoa, method=bray")

The result is that my data on the plot are grouped by the replicates and not by study groups. How can I work this out?

Kind regards

This means that the variance between your groups is larger than between your reps.

I don't exactly understand what your research question is. Do you want to find differences (genes?) between groups? And what about your design, are these technical replicates? Biological replicates? Is it paired-sample analysis?

You might want to explain more about your experiment.

310these are biological replicates. And the question is exactly about the design. Where in code to put this and how?

rep1,rep2,rep3 are biological replicates and group1,group2,group3 are study groups

0PCA is to show the variance or similarity within your data. In your case it shows that your replicates are more similar than your groups, I assume from your post.

If you want to know differences between your groups, you should do statistical analysis and use tests. For this you need a proper design (e.g., are your replicates the same in all groups, hence paired-sample analysis or not?).

But I don't know what your research question is!

310