I’m getting a lot of non-DE genes after I do “t-test overest var” between clusters. Same happens with wilcoxon. I did this on an anndata object that I scaled after mnn_correct and clustering.
## Scale raw mtx b = sc.AnnData(X = corr_data.raw.X, var = corr_data.raw.var, obs = corr_data.obs) # If False, omit zero-centering variables, which allows to handle # sparse input efficiently. sc.pp.scale(b, max_value = 10, zero_center = False) bdata = corr_data.copy() del bdata.raw bdata.raw = b
In Seurat there’s parameters that allow a parameter to exclude genes that don’t meet extra criteria, so to get rid of these streaks that occur across the heatmap. I haven’t tried this function yet but is this the function I should use to try doing the same? https://scanpy.readthedocs.io/en/stable/api/scanpy.tl.filter_rank_genes_groups.html
This is discussed here: Why max_out_group_fraction in sc.tl.filter_rank_genes_groups set to 0.5