update batch param in top_markers function.

R/AllGenerics.R

@@ -73,6 +73,7 @@ setGeneric(
            label,
            n = 10,
            use.glm = TRUE,
+           batch = NULL,
            scale = TRUE,
            use.mgm = TRUE,
            softmax = TRUE,

R/top_markers-methods.R

@@ -10,6 +10,7 @@ setMethod(
            label,
            n = 10,
            use.glm = TRUE,
+           batch = NULL,
            scale = TRUE,
            use.mgm = TRUE,
            softmax = TRUE,
@@ -20,6 +21,8 @@ setMethod(
       "label must be atomic and the same length as data column number" =
         is.atomic(label) & length(label) == ncol(data),
       "use.glm must be logical" = is.logical(use.glm),
+      "batch must be atomic and the same length as data column number" =
+        (is.atomic(batch) & length(batch) == ncol(data)) | is.null(batch),
       "scale must be logical" = is.logical(scale),
       "use.mgm must be logical" = is.logical(use.mgm),
       "softmax must be logical" = is.logical(softmax)
@@ -30,6 +33,7 @@ setMethod(
       label = label,
       n = n,
       use.glm = use.glm,
+      batch = batch,
       scale = scale,
       use.mgm = use.mgm,
       softmax = softmax,
@@ -49,6 +53,7 @@ setMethod(
            label,
            n = 10,
            use.glm = TRUE,
+           batch = NULL,
            scale = TRUE,
            use.mgm = TRUE,
            softmax = TRUE,
@@ -57,19 +62,25 @@ setMethod(
     ## check
     stopifnot(
       "label must be a single character for se object" =
-        is.character(label) & length(label) == 1
+        is.character(label) & length(label) == 1,
+      "batch must be NA or a single character for se object" =
+        is.null(batch) | (is.character(batch) & length(batch) == 1)
     )
 
     ## get expr
     expr <- SummarizedExperiment::assay(data, i = slot)
     ## get label
     label <- SummarizedExperiment::colData(data)[[label]]
+    ## get batch
+    if(!is.null(batch))
+      batch <- SummarizedExperiment::colData(data)[[batch]]
 
     top_m <- top_markers(
       data = expr,
       label = label,
       n = n,
       use.glm = use.glm,
+      batch = batch,
       scale = scale,
       use.mgm = use.mgm,
       softmax = softmax,

R/top_markers.R

@@ -14,6 +14,7 @@
 #' top_markers_init(data, label = rep(c("A", "B"), 5))
 top_markers_init <- function(data, label, n = 10,
                              use.glm = TRUE,
+                             batch = NULL,
                              scale = TRUE,
                              use.mgm = TRUE,
                              softmax = TRUE,
@@ -22,6 +23,7 @@ top_markers_init <- function(data, label, n = 10,
     data <- top_markers_glm(
       data = data,
       label = label,
+      batch = batch,
       n = n,
       scale = scale,
       use.mgm = use.mgm,
@@ -151,6 +153,8 @@ top_markers_glm <- function(data, label, n = 10,
     ## model with group label only
     betas <- apply(data, 1, \(s) glm(s ~ 0 + label, family = family)$coef)
   } else {
+    ## factorize batch label
+    batch <- factor(batch)
     ## model with both group and batch label
     betas <- apply(data, 1, \(s) glm(s ~ 0 + label + batch, family = family)$coef)
     ## only extract betas of group label

tests/testthat/test-top_markers.R

@@ -2,10 +2,11 @@ test_that("top markers works", {
   ## sim data
   expr <- matrix(rgamma(100, 2), 10, dimnames = list(1:10))
   label <- rep(c("A", "B"), 5)
+  batch <- sample(seq_len(2), 10, replace = TRUE)
 
   se <- SummarizedExperiment::SummarizedExperiment(
     assays = list(counts = expr),
-    colData = data.frame(group = label)
+    colData = data.frame(group = label, batch = batch)
   )
 
   ## test matrix
@@ -50,4 +51,14 @@ test_that("top markers works", {
     slot = "counts"
   )
   expect_s3_class(res, "data.frame")
+
+  ## test batch
+  res <- top_markers(
+    data = se,
+    label = "group",
+    batch = "batch",
+    n = 3,
+    slot = "counts"
+  )
+  expect_s3_class(res, "data.frame")
 })