Only extract indices of the top genes from scoreMarkers, for efficiency.

Author: LTLA

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: SingleR
 Title: Reference-Based Single-Cell RNA-Seq Annotation
-Version: 2.13.4
-Date: 2026-03-09
+Version: 2.13.5
+Date: 2026-04-09
 Authors@R: c(person("Dvir", "Aran", email="dvir.aran@ucsf.edu", role=c("aut", "cph")),
     person("Aaron", "Lun", email="infinite.monkeys.with.keyboards@gmail.com", role=c("ctb", "cre")),
     person("Daniel", "Bunis", role="ctb"),
@@ -33,7 +33,7 @@ Suggests:
     BiocStyle,
     BiocParallel,
     SingleCellExperiment,
-    scrapper (>= 1.3.14),
+    scrapper (>= 1.5.16),
     scRNAseq,
     ggplot2,
     pheatmap,

R/trainSingleR.R

@@ -437,7 +437,8 @@ trainSingleR <- function(
                 compute.delta.detected=FALSE,
                 compute.delta.mean=FALSE,
                 compute.auc=compute.auc,
-                compute.cohens.d=compute.cohens.d
+                compute.cohens.d=compute.cohens.d,
+                top.index.only=TRUE
             ),
             de.args
         )
@@ -450,7 +451,7 @@ trainSingleR <- function(
             if (g1 == g2) {
                 pairwise[[g1]][[g2]] <- character(0)
             } else {
-                pairwise[[g1]][[g2]] <- all.genes[pairwise[[g1]][[g2]]$index]
+                pairwise[[g1]][[g2]] <- all.genes[pairwise[[g1]][[g2]]]
             }
         }
     }