Updated version to 0.1.2

Updated the version number to go in preparation for new stable release.

also, minor changes to examples for var_OR_get_meta_or_gene() and which_cells() functions caught in the Check Package process

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: DittoSeq
 Type: Package
 Title: User Friendly Single-cell and Bulk RNA Sequencing Visualization
-Version: 0.1.0
+Version: 0.1.2
 Author: Daniel Bunis
 Maintainer: Daniel Bunis <daniel.bunis@ucsf.edu>
 Description: A set of functions for generating publication-ready (sc)RNAseq figures with as simple of coding input as possible.  This package attempts to be colorblind friendly by default & novice-to-coding user-friendly.  It mimics and extends Seurat plotting capabilities, and enables side-by-side analysis of bulk and scRNAseq data through the creation of a Seurat-like S4 data structure for the analysis of bulk sequencing data.

R/DittoSeq.R

@@ -1254,7 +1254,7 @@ all_cells <- function(object = DEFAULT){
 #' @return Given a logical or a list of names (or NULL) will output the list of cells names.  For retrieval / standardization.
 #' @examples
 #' pbmc <- Seurat::pbmc_small
-#' which_cells(meta("ident")=="0", "pbmc")
+#' which_cells(meta("ident","pbmc")=="0", "pbmc")
 
 which_cells <- function(cells.use, object = DEFAULT){
   all.cells <- all_cells(object)
@@ -1324,7 +1324,7 @@ S4_2string <- function(object = DEFAULT){
 #' @return determines what type of var is given, and outputs the gene expression data, metadata data, or clustering data.
 #' @examples
 #' pbmc <- Seurat::pbmc_small
-#' var_OR_get_meta_or_gene("CD34", "pbmc", "normalized")
+#' var_OR_get_meta_or_gene("CD14", "pbmc", "normalized")
 #' var_OR_get_meta_or_gene("ident", "pbmc")
 #' var_OR_get_meta_or_gene("nUMI", "pbmc")