I have two conditions, about 50 samples for each condition, and for each sample - a set of 9 proportions. The proportions are estimates of the proportion of 9 cell types of this patient.
Clarification : The estimates are of the proportion of the cell types in the tissue of the specific sample. It was arrived at using deconvolution software. The software does not estimate the total number of cells, hence I have the estimate of the proportion but not the sample size (not the denominator\numerator of the proportion).
I want to test statistically the proportions of which cell type change between the two conditions.
Clarification : There are 9 estimates of proportions for each sample, which correspond to 9 distinct categories (cell types). Every sample has all 9 categories represented. I want to test across which categories (cell-types), the change is significant between the two conditions. About 50 samples in each condition).
Cell A and cells C proportions probably change between the two conditions (G1&G2) while cell B proportions definitely do not.
What statistical test would be suitable?
I thought of averaging all proportions for each of the groups and applying something like a t-test, but the proportions are bounded between zero and one, hence I don't think it would be suitable. Also, (not sure how important this is) I have no theoretical reasons to suppose normal distribution.
The second problem I see is that the proportions of the different cells are not independent. If cell A proportions are extremely high in a specific patient, the proportions of other cells are more likely to be low. Hence, I am more likely to get false positives compared to a situation where the proportions of each cell type would be independent from the others.