I did compute the composition of cell type in each condition as below
library("scProportionTest") seurat_integrated <- system.file("seurat_integrated", "seurat_labelled_0.7.rds", package = "scProportionTest") seurat_integrated <- readRDS("seurat_labelled_0.7.rds") prop_test <- sc_utils(seurat_integrated)
prop_test <- permutation_test( prop_test, cluster_identity = "major", sample_1 = "als", sample_2 = "control", sample_identity = "status" ) pdf("major_proportion_compare_between_status.pdf", height=5, width=10) permutation_plot(prop_test) dev.off()
In my case, the proportion of cell type in different affected status are as below
But when I did permutation I expected to see sth not that different. But the result is as below
So, if the result is comparison of sample1=ALS compared to sample 2=control is it true that most of the subpopulation are overrepresented in ALS in contrast to the first plot? For example, in the first plot the OL population are overrepresented in ALS but in the second it's not. I mean my result in permutation is not consistent with the marplot. I would like to know whether I'm interpreting anything wrong. I appreciate any help
The images seem to be missing from your post
Oh, I'm sorry. I already posted it in here the correct way of analyzing cell proportions in singlecell data. I've added the images
@rpolicastro I really appreciate it if you could help me with this question