fix more notes

R/compute_similarity.R

@@ -282,7 +282,7 @@ vector_similarity <- function(vec1, vec2, compute_method, ...) {
     }
 
     if (!(compute_method %in% c("cosine", "kl_divergence"))) {
-        stop(paste(compute_method, "not implemented"), call. = FALSE)
+        stop(compute_method, " not implemented", call. = FALSE)
     }
 
     if (compute_method == "kl_divergence") {

R/main.R

@@ -132,7 +132,7 @@ clustify.default <- function(input,
     expand_unassigned = FALSE,
     ...) {
     if (!compute_method %in% clustifyr_methods) {
-        stop(paste(compute_method, "correlation method not implemented"),
+        stop(compute_method, " correlation method not implemented",
             call. = FALSE
         )
     }

R/object_access.R

@@ -38,7 +38,17 @@ so_pbmc <- function() {
 #' @export
 sce_pbmc <- function() {
   x <- pbmc_example_data()
-  md <- x$metadata[, c(1:5, 7)]
+
+  cols_to_keep <- c(
+    "orig.ident",
+    "nCount_RNA",
+    "nFeature_RNA",
+    "percent.mt",
+    "RNA_snn_res.0.5",
+    "classified"
+  )
+
+  md <- x$metadata[, cols_to_keep]
   # rename to more sce-like names
   colnames(md) <- c("cell_source", 
                     "sum",
@@ -295,7 +305,7 @@ seurat_ref.Seurat <- function(seurat_object,
             SeuratObject::DefaultAssay(seurat_object) <- og_assay
         }
     } else {
-        stop("warning, not seurat3 object")
+        stop("Input is not a compatible Seurat object")
     }
 
     temp_res <- average_clusters(

vignettes/clustifyr.Rmd

@@ -239,7 +239,8 @@ res <- clustify(
   obj_out = TRUE  # output Seurat object with cell type inserted as "type" column
 )
 
-res@meta.data[1:10, c("type", "r")]
+# type and r are stored in the meta.data 
+res[[c("type", "r")]][1:10, ]
 ```
 
 # Building reference matrix from single cell expression matrix