Use mean.fxn for FindMarkers.SCTAssay

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: Seurat
-Version: 4.2.0
+Version: 4.2.0.9001
 Date: 2022-09-21
 Title: Tools for Single Cell Genomics
 Description: A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031>, and Hao, Hao, et al (2020) <doi:10.1101/2020.10.12.335331> for more details.

R/differential_expression.R

@@ -752,6 +752,12 @@ FindMarkers.SCTAssay <- function(
     'scale.data' = GetAssayData(object = object, slot = "counts"),
     numeric()
   )
+  if (is.null(x = mean.fxn)){
+    mean.fxn <- function(x) {
+      return(log(x = rowMeans(x = expm1(x = x)) + pseudocount.use, base = base))
+
+    }
+  }
   fc.results <- FoldChange(
     object = object,
     slot = data.slot,
@@ -761,8 +767,7 @@ FindMarkers.SCTAssay <- function(
     pseudocount.use = pseudocount.use,
     mean.fxn = mean.fxn,
     fc.name = fc.name,
-    base = base,
-    norm.method = 'LogNormalize' # do expm1 on data slot
+    base = base
     )
   de.results <- FindMarkers(
     object = data.use,
@@ -785,7 +790,6 @@ FindMarkers.SCTAssay <- function(
     pseudocount.use = pseudocount.use,
     fc.results = fc.results,
     densify = densify,
-    norm.method = 'LogNormalize', # do expm1 on data slot
     ...
   )
   return(de.results)