Documentation and devtools::check()

NAMESPACE

@@ -5,11 +5,16 @@ S3method(clusterJF,prcomp)
 S3method(clusterJF,tbl)
 S3method(dimreductJF,matrix)
 S3method(dimreductJF,prcomp)
+S3method(extract_values,matrix)
+S3method(extract_values,prcomp)
 export(app_server)
 export(app_ui)
 export(clusterJF)
 export(compositionJF)
 export(dimreductJF)
+export(extract_sb_loadings)
+export(extract_sb_values)
+export(extract_values)
 export(marker_heatJF)
 export(run_app)
 export(save_flowdata)
@@ -33,8 +38,6 @@ importFrom(fastcluster,hclust)
 importFrom(ggrepel,geom_label_repel)
 importFrom(ggsci,pal_d3)
 importFrom(ggsci,pal_igv)
-importFrom(gridExtra,arrangeGrob)
-importFrom(gridExtra,grid.arrange)
 importFrom(reshape2,dcast)
 importFrom(reshape2,melt)
 importFrom(rlang,.data)

R/app_server.R

@@ -629,7 +629,7 @@ app_server <- function(input, output, session) {
                      meta           = meta_mat(),
                      grp            = input$meta_val) %>%
 
-        rename(PC1 = X1, PC2 = X2) %>%
+        rename(PC1 = .data$X1, PC2 = .data$X2) %>%
 
         utils::write.table(file, sep='\t', quote=FALSE, row.names=FALSE)
     })
@@ -674,7 +674,7 @@ app_server <- function(input, output, session) {
                      meta           = meta_mat(),
                      grp            = input$meta_val) %>%
 
-        rename(UMAP_1 = X1, UMAP_2 = X2) %>%
+        rename(UMAP_1 = .data$X1, UMAP_2 = .data$X2) %>%
 
         utils::write.table(file, sep='\t', quote=FALSE, row.names=FALSE)
     })
@@ -711,7 +711,7 @@ app_server <- function(input, output, session) {
                      meta           = meta_mat(),
                      grp            = input$meta_val) %>%
 
-        rename(tSNE_1 = X1, tSNE_2 = X2) %>%
+        rename(tSNE_1 = .data$X1, tSNE_2 = .data$X2) %>%
 
         utils::write.table(file, sep='\t', quote=FALSE, row.names=FALSE)
     })

R/extract_values.R

@@ -10,7 +10,7 @@
 #' @param grp Character value identifying the column of `meta` to use for group identifier
 #' @param ... Other objects passed to methods of `extract_values`
 #'
-#' @value A tibble with values for SampleID, Group, Cluster, PC/vector 1, and PC/vector 2
+#' @return A tibble with values for SampleID, Group, Cluster, PC/vector 1, and PC/vector 2
 #' @export
 #' @import dplyr
 #' @importFrom rlang .data
@@ -34,6 +34,11 @@ extract_values.prcomp <- function(clustered_data, ids, meta, grp, ...)
 #' @export
 extract_values.matrix <- function(clustered_data, ids, meta, grp, ...)
 {
+  # fix "no visible global function definition" warnings in devtools::check()
+  # (can't use `.data$` inside of dplyr::select)
+  SampleID <- Group <- X1 <- X2 <- NULL
+
+  # create data.frame to return
   retval <- tibble(SampleID = ids,
                    X1       = clustered_data[,1],
                    X2       = clustered_data[,2])
@@ -70,10 +75,15 @@ extract_values.matrix <- function(clustered_data, ids, meta, grp, ...)
 #' @param ids Character vector of ids for each row in `clustered_data$x`, corresponding to labels in `grps`
 #' @param meta Data frame containing translation from id to group
 #' @param grp Character value identifying the column of `meta` to use for group identifier
-#' @value a data frame with values for SampleID, and Group, PC1, and PC2
+#' @return a data frame with values for SampleID, Group, PC1, and PC2
 #' @export
+#' @import dplyr
 extract_sb_values <- function(clustered_data, ids, meta, grp)
 {
+  # fix "no visible global function definition" warnings in devtools::check()
+  # (can't use `.data$` inside of dplyr::select)
+  SampleID <- Group <- PC1 <- PC2 <- NULL
+
   # pull principal components from sb_pca()
   tibble(SampleID = ids,
          PC1      = clustered_data$x[,'PC1'],
@@ -93,8 +103,9 @@ extract_sb_values <- function(clustered_data, ids, meta, grp)
 #' Extract loadings from sample based PCA
 #'
 #' @param clustered_data Object containing clustered data (expects output from `prcomp`)
-#' @value a data frame with loadings for PC1 and PC2 for each Cluster
+#' @return a data frame with loadings for PC1 and PC2 for each Cluster
 #' @export
+#' @import dplyr
 extract_sb_loadings <- function(clustered_data)
 {
   # pull loadings from clustered_data

inst/WORDLIST

@@ -5,20 +5,27 @@ NIAID
 RData
 RStudio
 Rtsne
+SampleID
 UMAP
 clusterJF
 cytometry
 devtools
 flowdata
 ggplot
 github
+grps
 https
 interpretable
 io
 kmeans
+loadings
 niaid
 prcomp
+sb
 scRNA
+tSNE
 testData
+tibble
+tsne
 uamp
 umap