@@ -47,10 +47,11 @@ setGeneric("train_classifier",

 #' 

 #' @param seurat_tag_slot string, name of slot in cell meta data 

 #' indicating cell tag/label in the training object.

-#' Strings indicating cell types are expected in this slot. 

+#' Strings indicating cell types are expected in this slot.

 #' For \code{\link{Seurat}} object, default value is "active.ident".  

-#' Expected values are string or binary/logical, 

-#' 0/"no"/F/FALSE: not being new cell type, 1/"yes"/T/TRUE: being new cell type.

+#' Expected values are string (A-Z, a-z, 0-9, no special character accepted) 

+#' or binary/logical, 0/"no"/F/FALSE: not being new cell type, 

+#' 1/"yes"/T/TRUE: being new cell type.

 #' @param seurat_parent_tag_slot string, name of a slot in cell meta data 

 #' indicating assigned/predicted cell type. Default is "predicted_cell_type". 

 #' This slot would have been filled automatically 

@@ -193,8 +194,9 @@ setMethod("train_classifier", c("train_obj" = "Seurat"),

 #' @param sce_tag_slot string, name of annotation slot indicating 

 #' cell tag/label in the training object.

 #' For \code{\link{SingleCellExperiment}} object, default value is "ident".  

-#' Expected values are string or binary/logical, 

-#' 0/"no"/F/FALSE: not being new cell type, 1/"yes"/T/TRUE: being new cell type.

+#' Expected values are string (A-Z, a-z, 0-9, no special character accepted) 

+#' or binary/logical, 0/"no"/F/FALSE: not being new cell type, 

+#' 1/"yes"/T/TRUE: being new cell type.

 #' @param sce_parent_tag_slot string, name of a slot in cell meta data 

 #' indicating pre-assigned/predicted cell type. 

 #' Default field is "predicted_cell_type".

@@ -339,8 +341,8 @@ setGeneric("test_classifier", function(test_obj, classifier,

 #' indicating cell tag/label in the testing object.

 #' Strings indicating cell types are expected in this slot. 

 #' For \code{\link{Seurat}} object, default value is "active.ident". 

-#' Expected values is string or binary/logical, 

-#' 0/"no"/F/FALSE: not being new cell type, 

+#' Expected values are string (A-Z, a-z, 0-9, no special character accepted) 

+#' or binary/logical, 0/"no"/F/FALSE: not being new cell type, 

 #' 1/"yes"/T/TRUE: being new cell type.

 #' @param seurat_parent_tag_slot string, name of tag slot in cell meta data

 #' indicating pre-assigned/predicted parent cell type. 

@@ -444,8 +446,8 @@ setMethod("test_classifier", c("test_obj" = "Seurat",

 #' indicating cell tag/label in the testing object.

 #' Strings indicating cell types are expected in this slot. 

 #' Default value is "ident".  

-#' Expected values are string or binary/logical, 

-#' 0/"no"/F/FALSE: not being new cell type, 

+#' Expected values are string (A-Z, a-z, 0-9, no special character accepted) 

+#' or binary/logical, 0/"no"/F/FALSE: not being new cell type, 

 #' 1/"yes"/T/TRUE: being new cell type.

 #' @param sce_parent_tag_slot string, name of tag slot in cell meta data

 #' indicating pre-assigned/predicted parent cell type. 

Binary files a/data/default_models.rda and b/data/default_models.rda differ

@@ -69,8 +69,8 @@ the new_models.rda file.}

 indicating cell tag/label in the testing object.

 Strings indicating cell types are expected in this slot. 

 For \code{\link{Seurat}} object, default value is "active.ident". 

-Expected values is string or binary/logical, 

-0/"no"/F/FALSE: not being new cell type, 

+Expected values are string (A-Z, a-z, 0-9, no special character accepted) 

+or binary/logical, 0/"no"/F/FALSE: not being new cell type, 

 1/"yes"/T/TRUE: being new cell type.}

 \item{seurat_parent_tag_slot}{string, name of tag slot in cell meta data

@@ -90,8 +90,8 @@ Default to "counts", which contains unnormalized data.}

 indicating cell tag/label in the testing object.

 Strings indicating cell types are expected in this slot. 

 Default value is "ident".  

-Expected values are string or binary/logical, 

-0/"no"/F/FALSE: not being new cell type, 

+Expected values are string (A-Z, a-z, 0-9, no special character accepted) 

+or binary/logical, 0/"no"/F/FALSE: not being new cell type, 

 1/"yes"/T/TRUE: being new cell type.}

 \item{sce_parent_tag_slot}{string, name of tag slot in cell meta data

@@ -78,10 +78,11 @@ new_models.rda file.}

 \item{seurat_tag_slot}{string, name of slot in cell meta data 

 indicating cell tag/label in the training object.

-Strings indicating cell types are expected in this slot. 

+Strings indicating cell types are expected in this slot.

 For \code{\link{Seurat}} object, default value is "active.ident".  

-Expected values are string or binary/logical, 

-0/"no"/F/FALSE: not being new cell type, 1/"yes"/T/TRUE: being new cell type.}

+Expected values are string (A-Z, a-z, 0-9, no special character accepted) 

+or binary/logical, 0/"no"/F/FALSE: not being new cell type, 

+1/"yes"/T/TRUE: being new cell type.}

 \item{seurat_parent_tag_slot}{string, name of a slot in cell meta data 

 indicating assigned/predicted cell type. Default is "predicted_cell_type". 

@@ -99,8 +100,9 @@ and "scale.data". Default to "counts", which contains unnormalized data.}

 \item{sce_tag_slot}{string, name of annotation slot indicating 

 cell tag/label in the training object.

 For \code{\link{SingleCellExperiment}} object, default value is "ident".  

-Expected values are string or binary/logical, 

-0/"no"/F/FALSE: not being new cell type, 1/"yes"/T/TRUE: being new cell type.}

+Expected values are string (A-Z, a-z, 0-9, no special character accepted) 

+or binary/logical, 0/"no"/F/FALSE: not being new cell type, 

+1/"yes"/T/TRUE: being new cell type.}

 \item{sce_parent_tag_slot}{string, name of a slot in cell meta data 

 indicating pre-assigned/predicted cell type. 

@@ -104,9 +104,14 @@ To launch cell type identification, we simply call the `classify_cells`

 function. A detailed description of all parameters can be found through

 the function's help page `?classify_cells`.

+Here we use only 3 classifiers for B cells, T cells and NK cells to reduce 

+computational cost of this vignette. If users want to use all pretrained 

+classifiers on their dataset, `cell_types = 'all'` can be used.

 ```{r}

 seurat.obj <- classify_cells(classify_obj = tirosh_mel80_example, 

-                             cell_types = 'all', path_to_models = 'default')

+                             seurat_assay = 'RNA', seurat_slot = 'data',

+                             cell_types = c('B cells', 'NK', 'T cells'), 

+                             path_to_models = 'default')

 ```

 #### Parameters

@@ -130,7 +135,7 @@ but with additional columns in the metadata table.

 ```{r}

 # display the additional metadata fields

-seurat.obj[[]][c(20:30), c(8:21)]

+seurat.obj[[]][c(50:60), c(8:16)]

 ```

 New columns are: