replace calculateRDA with getRDA and calculateCCA with getCCA

R/plotCCA.R

@@ -6,10 +6,10 @@
 #'
 #' @param object a
 #'   \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-constructor]{TreeSummarizedExperiment}}
-#'   or a matrix of weights. The latter is returned as output from \code{\link[mia:runCCA]{calculateRDA}}.
+#'   or a matrix of weights. The latter is returned as output from \code{\link[mia:runCCA]{getRDA}}.
 #' 
 #' @param dimred A string or integer scalar indicating the reduced dimension to
-#'   plot. This is the output of \code{\link[mia:runCCA]{runRDA}} and resides in
+#'   plot. This is the output of \code{\link[mia:runCCA]{addRDA}} and resides in
 #'   \code{reducedDim(tse, dimred)}.
 #' 
 #' @param add.ellipse One of \code{c(TRUE, FALSE, "fill", "colour", "color")},
@@ -85,10 +85,10 @@
 #' for supervised ordination of microbiome data. Either a
 #' \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-constructor]{TreeSummarizedExperiment}}
 #' or a matrix object is supported as input. When the input is a
-#' TreeSummarizedExperiment, this should contain the output of runRDA
+#' TreeSummarizedExperiment, this should contain the output of addRDA
 #' in the reducedDim slot and the argument \code{dimred} needs to be defined.
 #' When the input is a matrix, this should be returned as output from
-#' calculateRDA. However, the first method is recommended because it provides
+#' getRDA. However, the first method is recommended because it provides
 #' the option to adjust aesthetics to the colData variables through the
 #' arguments inherited from \code{\link[scater:plotReducedDim]{plotReducedDim}}.
 #' 
@@ -104,7 +104,7 @@
 #' tse <- enterotype
 #'  
 #' # Run RDA and store results into TreeSE
-#' tse <- runRDA(tse,
+#' tse <- addRDA(tse,
 #'               formula = assay ~ ClinicalStatus + Gender + Age,
 #'               FUN = vegan::vegdist,
 #'               distance = "bray",
@@ -135,11 +135,11 @@
 #'         add.vectors = FALSE)
 #'  
 #' # Calculate RDA as a separate object
-#' rda_mat <- calculateRDA(tse,
-#'                         formula = assay ~ ClinicalStatus + Gender + Age,
-#'                         FUN = vegan::vegdist,
-#'                         distance = "bray",
-#'                         na.action = na.exclude)
+#' rda_mat <- getRDA(tse,
+#'                   formula = assay ~ ClinicalStatus + Gender + Age,
+#'                   FUN = vegan::vegdist,
+#'                   distance = "bray",
+#'                   na.action = na.exclude)
 #'  
 #' # Create RDA plot from RDA matrix
 #' plotRDA(rda_mat)
@@ -330,9 +330,9 @@ setMethod("plotRDA", signature = c(object = "matrix"),
             expl_var <- summary(rda)$concont$importance[2, ]*100
         } else{
             # If it cannot be found, give warning
-            warning(paste("RDA/CCA object was not found. Please compute",
-                          "RDA/CCA by using runCCA or calculateCCA."),
-                    call. = FALSE)
+            warning(
+                paste("RDA/CCA object was not found. Please compute",
+                "RDA/CCA by using addCCA or getCCA."), call. = FALSE)
         }
     }
 
@@ -364,9 +364,9 @@ setMethod("plotRDA", signature = c(object = "matrix"),
             vector_data[["group"]] <- rownames(vector_data)
         } else{
             # If it cannot be found, give warning
-            warning(paste("RDA/CCA object was not found. Please compute RDA/CCA",
-                          "by using runCCA or calculateCCA."),
-                    call. = FALSE)
+            warning(
+                paste("RDA/CCA object was not found. Please compute RDA/CCA",
+                    "by using addCCA or getCCA."), call. = FALSE)
         }
     }
 
@@ -429,9 +429,9 @@ setMethod("plotRDA", signature = c(object = "matrix"),
             vector_data[["vector_label"]] <- vector_label
         } else{
             # If it cannot be found, give warning
-            warning(paste("Significance data was not found. please compute",
-                          "CCA/RDA by using runCCA or calculateCCA."),
-                    call. = FALSE)
+            warning(
+                paste("Significance data was not found. please compute",
+                    "CCA/RDA by using addCCA or getCCA."), call. = FALSE)
         }
     }
 

tests/testthat/test-plotCCA.R

@@ -9,8 +9,8 @@ test_that("plot RDA/CCA", {
   expect_error(plotRDA(tse, "RDA"), "'dimred' must specify reducedDim.")
 
   # Run/calculate RDA
-  tse <- runRDA(tse, assay ~ patient_status + cohort)
-  rda <- calculateRDA(tse, assay ~ patient_status + cohort)
+  tse <- addRDA(tse, assay ~ patient_status + cohort)
+  rda <- getRDA(tse, assay ~ patient_status + cohort)
 
   # Minimal functionality
   expect_no_error(plotRDA(tse, "RDA"))