I have added a new assay to my seurat object and I want to test for differential expression of all these features by a condition in a metadata column (which for this example can take the values of "condition1" or "condition2"). My command looks like:

dea <- FindMarkers(obj, ident.1 = "condition1", ident.2 = "condition2", 
                   group.by = "condition", assay = "another_assay", features = rownames(obj@assays$another_assay),
                   test.use = "wilcox",  min.pct = 0, logfc.threshold = 0, base = 2)

This does not return the test results for all the features in the assay :-/ I know the default for features = is all genes in the assay but i was not getting all the features, so i specifically put the rownames of the assay to specify it, but i still get less than I would expect.

I have also tried logfc.threshold = -Inf, I get the same output.

I have tried setting min.diff.pct = 0, I get even fewer features.

In addition to this, I have a question regarding the output I do get. The documentation says:

avg_logFC: log fold-chage of the average expression between the two groups.

For a given feature, I'm getting an avg_log2FC of 8.5 . Just to verify, I did:

feature1 <- data.frame(V1=GetAssayData(obj, assay = "another_assay")["feature1",])
feature1 <- merge(feature1, data.frame(condition=obj$condition), by='row.names')

avg_cond1 <- mean(feature1[which(feature1$condition == "condition1"), "V1"])
avg_cond2 <- mean(feature1[which(feature1$condition == "condition2"), "V1"])

log2(avg_cond1 / avg_cond2)

This does not equal 8.5

Any idea on what I'm doing wrong?

I'm running R 4.0.2 with Seurat 4.0.0

UPDATE: This gitHub issue solves my second question. However, I have a follow up question:

In their avg_logFC calculation they calculate the mean of e^x - 1 (where x is the expression values for a gene) and then log it (line 176/7).

My question is: Why do they calculate the mean of e^x - 1 instead of just the mean of x?