Merge pull request #370 from cole-trapnell-lab/news_red_dim_mods

prepare for version 0.2.2.0 and fix typos
cole-trapnell-lab · Jun 10, 2020 · 161c121 · 161c121
2 parents ebb9759 + 0a772b6
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: monocle3
 Title: Clustering, differential expression, and trajectory analysis for single-
     cell RNA-Seq
-Version: 0.2.1.9
+Version: 0.2.2
 Authors@R: 
     person(given = "Hannah",
            family = "Pliner",

diff --git a/NEWS.md b/NEWS.md
@@ -1,3 +1,24 @@
+# monocle3 0.2.2
+
+### Changes
+* Added load_mm_data() to load data from matrix market sparse file and gene and cell data files.
+* Added rann.k parameter to learn_graph().
+* Added speedglm.maxiter parameter to top_marker().
+
+### Bug fixes
+* Fixed combine_cds() issues.
+* Fixed learn_graph(use_partition=FALSE) issue
+* Fixed batchelor::fastMNN(pc.input) deprecation issue
+* Fixed choose_graph_segments() issue.
+* Fixed missing gaussian family in fit_models().
+* Fixed add pseudocount to violin plot.
+* Fixed add detect_genes() to fit_models() if needed.
+* Fixed compare_models() issues.
+* Fixed check for undefined values in fit_models() formula.
+* Fixed plot_cells() plotting order issue.
+* Fixed find_gene_modules() run-to-run variation issue.
+* Fixed rlist package namespace collision.
+* Fixed allow short gene names in aggregate_gene_expression(gene_group_df).
 
 # monocle3 0.2.0
 

diff --git a/R/cluster_cells.R b/R/cluster_cells.R
@@ -93,7 +93,7 @@ cluster_cells <- function(cds,
   assertthat::assert_that(!is.null(reducedDims(cds)[[reduction_method]]),
                           msg = paste("No dimensionality reduction for",
                                       reduction_method, "calculated.",
-                                      "Please run reduce_dimensions with",
+                                      "Please run reduce_dimension with",
                                       "reduction_method =", reduction_method,
                                       "before running cluster_cells"))
 

diff --git a/R/cluster_genes.R b/R/cluster_genes.R
@@ -62,7 +62,7 @@ find_gene_modules <- function(cds,
   assertthat::assert_that(!is.null(reducedDims(cds)[[reduction_method]]),
                           msg = paste("No dimensionality reduction for",
                                       reduction_method, "calculated.",
-                                      "Please run reduce_dimensions with",
+                                      "Please run reduce_dimension with",
                                       "reduction_method =", reduction_method,
                                       "before running cluster_cells"))
 

diff --git a/R/learn_graph.R b/R/learn_graph.R
@@ -17,7 +17,7 @@
 #' technical factors) to "subtract" from the data so it doesn't contribute to
 #' the trajectory. The function \code{learn_graph} is the fourth step in the
 #' trajectory building process after \code{preprocess_cds},
-#' \code{reduce_dimensions}, and \code{cluster_cells}. After
+#' \code{reduce_dimension}, and \code{cluster_cells}. After
 #' \code{learn_graph}, \code{order_cells} is typically called.
 #'
 #' @section Optional \code{learn_graph_control} parameters:
@@ -139,7 +139,7 @@ learn_graph <- function(cds,
   assertthat::assert_that(!is.null(reducedDims(cds)[[reduction_method]]),
                           msg = paste("No dimensionality reduction for",
                                       reduction_method, "calculated.",
-                                      "Please run reduce_dimensions with",
+                                      "Please run reduce_dimension with",
                                       "reduction_method =", reduction_method,
                                       "and cluster_cells before running",
                                       "learn_graph."))

diff --git a/R/order_cells.R b/R/order_cells.R
@@ -37,7 +37,7 @@ order_cells <- function(cds,
   assertthat::assert_that(!is.null(reducedDims(cds)[[reduction_method]]),
                           msg = paste0("No dimensionality reduction for ",
                                       reduction_method, " calculated. ",
-                                      "Please run reduce_dimensions with ",
+                                      "Please run reduce_dimension with ",
                                       "reduction_method = ", reduction_method,
                                       ", cluster_cells, and learn_graph ",
                                       "before running order_cells."))

diff --git a/R/plotting.R b/R/plotting.R
@@ -77,7 +77,7 @@ plot_cells_3d <- function(cds,
   assertthat::assert_that(!is.null(reducedDims(cds)[[reduction_method]]),
                           msg = paste("No dimensionality reduction for",
                                       reduction_method, "calculated.",
-                                      "Please run reduce_dimensions with",
+                                      "Please run reduce_dimension with",
                                       "reduction_method =", reduction_method,
                                       "before attempting to plot."))
   low_dim_coords <- reducedDims(cds)[[reduction_method]]
@@ -410,7 +410,7 @@ plot_cells <- function(cds,
   assertthat::assert_that(!is.null(reducedDims(cds)[[reduction_method]]),
                           msg = paste("No dimensionality reduction for",
                                       reduction_method, "calculated.",
-                                      "Please run reduce_dimensions with",
+                                      "Please run reduce_dimension with",
                                       "reduction_method =", reduction_method,
                                       "before attempting to plot."))
   low_dim_coords <- reducedDims(cds)[[reduction_method]]

diff --git a/R/reduce_dimensions.R b/R/reduce_dimensions.R
@@ -11,8 +11,8 @@
 #' genes typically co-vary with one another, and so the dimensionality of the
 #' data can be reduced with a wide variety of different algorithms. Monocle3
 #' provides two different algorithms for dimensionality reduction via
-#' \code{reduce_dimensions} (UMAP and tSNE). The function
-#' \code{reduce_dimensions} is the second step in the trajectory building
+#' \code{reduce_dimension} (UMAP and tSNE). The function
+#' \code{reduce_dimension} is the second step in the trajectory building
 #' process after \code{preprocess_cds}.
 #'
 #' UMAP is implemented from the package uwot.

diff --git a/R/select_cells.R b/R/select_cells.R
@@ -16,7 +16,7 @@ choose_cells <- function(cds,
   assertthat::assert_that(!is.null(reducedDims(cds)[[reduction_method]]),
                           msg = paste0("No dimensionality reduction for ",
                                        reduction_method, " calculated. ",
-                                       "Please run reduce_dimensions with ",
+                                       "Please run reduce_dimension with ",
                                        "reduction_method = ", reduction_method,
                                        ", cluster_cells, and learn_graph ",
                                        "before running choose_cells"))
@@ -148,7 +148,7 @@ choose_graph_segments <- function(cds,
   assertthat::assert_that(!is.null(reducedDims(cds)[[reduction_method]]),
                           msg = paste0("No dimensionality reduction for ",
                                        reduction_method, " calculated. ",
-                                       "Please run reduce_dimensions with ",
+                                       "Please run reduce_dimension with ",
                                        "reduction_method = ", reduction_method,
                                        ", cluster_cells, and learn_graph ",
                                        "before running choose_graph_segments."))

diff --git a/man/learn_graph.Rd b/man/learn_graph.Rd
diff --git a/man/reduce_dimension.Rd b/man/reduce_dimension.Rd
diff --git a/tests/testthat/test-cluster_cells.R b/tests/testthat/test-cluster_cells.R
@@ -16,17 +16,17 @@ test_that("test cluster_cells error messages work", {
   skip_on_travis()
   expect_error(cds <- cluster_cells(cds),
                paste("No dimensionality reduction for UMAP calculated. Please",
-                     "run reduce_dimensions with reduction_method = UMAP",
+                     "run reduce_dimension with reduction_method = UMAP",
                      "before running cluster_cells"))
   cds <- preprocess_cds(cds)
   expect_error(cds <- cluster_cells(cds),
                paste("No dimensionality reduction for UMAP calculated. Please",
-                     "run reduce_dimensions with reduction_method = UMAP",
+                     "run reduce_dimension with reduction_method = UMAP",
                      "before running cluster_cells"))
   cds <- reduce_dimension(cds)
   expect_error(cds <- cluster_cells(cds, reduction_method = "tSNE"),
                paste("No dimensionality reduction for tSNE calculated. Please",
-                     "run reduce_dimensions with reduction_method = tSNE",
+                     "run reduce_dimension with reduction_method = tSNE",
                      "before running cluster_cells"))
 })
 
@@ -194,17 +194,17 @@ test_that("test cluster_cells error messages work", {
   skip_not_travis()
   expect_error(cds <- cluster_cells(cds),
                paste("No dimensionality reduction for UMAP calculated. Please",
-                     "run reduce_dimensions with reduction_method = UMAP",
+                     "run reduce_dimension with reduction_method = UMAP",
                      "before running cluster_cells"))
   cds <- preprocess_cds(cds)
   expect_error(cds <- cluster_cells(cds),
                paste("No dimensionality reduction for UMAP calculated. Please",
-                     "run reduce_dimensions with reduction_method = UMAP",
+                     "run reduce_dimension with reduction_method = UMAP",
                      "before running cluster_cells"))
   cds <- reduce_dimension(cds)
   expect_error(cds <- cluster_cells(cds, reduction_method = "tSNE"),
                paste("No dimensionality reduction for tSNE calculated. Please",
-                     "run reduce_dimensions with reduction_method = tSNE",
+                     "run reduce_dimension with reduction_method = tSNE",
                      "before running cluster_cells"))
 })
 

diff --git a/tests/testthat/test-graph_test.R b/tests/testthat/test-graph_test.R
@@ -21,10 +21,10 @@ cds <- learn_graph(cds, learn_graph_control=list(ncenter=1000), close_loop=TRUE)
 
 # test_that("test graph_test error messages work", {
 #   expect_error(cds <- graph_test(cds),
-#                "No dimensionality reduction for UMAP calculated. Please run reduce_dimensions with reduction_method = UMAP and partition_cells before running learn_graph.")
+#                "No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP and partition_cells before running learn_graph.")
 #   cds <- preprocess_cds(cds)
 #   expect_error(cds <- graph_test(cds),
-#                "No dimensionality reduction for UMAP calculated. Please run reduce_dimensions with reduction_method = UMAP and partition_cells before running learn_graph.")
+#                "No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP and partition_cells before running learn_graph.")
 #   cds <- reduce_dimension(cds)
 #   expect_error(cds <- graph_test(cds),
 #                "No cell partition for UMAP calculated. Please run partition_cells with reduction_method = UMAP before running learn_graph.")

diff --git a/tests/testthat/test-learn_graph.R b/tests/testthat/test-learn_graph.R
@@ -12,10 +12,10 @@ cds <- load_a549()
 test_that("test learn_graph error messages work", {
   skip_on_travis()
   expect_error(cds <- learn_graph(cds),
-               "No dimensionality reduction for UMAP calculated. Please run reduce_dimensions with reduction_method = UMAP and cluster_cells before running learn_graph.")
+               "No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP and cluster_cells before running learn_graph.")
   cds <- preprocess_cds(cds)
   expect_error(cds <- learn_graph(cds),
-               "No dimensionality reduction for UMAP calculated. Please run reduce_dimensions with reduction_method = UMAP and cluster_cells before running learn_graph.")
+               "No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP and cluster_cells before running learn_graph.")
   cds <- reduce_dimension(cds)
   expect_error(cds <- learn_graph(cds),
                "No cell clusters for UMAP calculated. Please run cluster_cells with reduction_method = UMAP before running learn_graph.")
@@ -67,10 +67,10 @@ cds <- load_a549()
 test_that("test learn_graph error messages work", {
   skip_not_travis()
   expect_error(cds <- learn_graph(cds),
-               "No dimensionality reduction for UMAP calculated. Please run reduce_dimensions with reduction_method = UMAP and cluster_cells before running learn_graph.")
+               "No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP and cluster_cells before running learn_graph.")
   cds <- preprocess_cds(cds)
   expect_error(cds <- learn_graph(cds),
-               "No dimensionality reduction for UMAP calculated. Please run reduce_dimensions with reduction_method = UMAP and cluster_cells before running learn_graph.")
+               "No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP and cluster_cells before running learn_graph.")
   cds <- reduce_dimension(cds)
   expect_error(cds <- learn_graph(cds),
                "No cell clusters for UMAP calculated. Please run cluster_cells with reduction_method = UMAP before running learn_graph.")

diff --git a/tests/testthat/test-order_cells.R b/tests/testthat/test-order_cells.R
@@ -12,7 +12,7 @@ cds <- load_a549()
 set.seed(100)
 test_that("order_cells error messages work", {
   skip_on_travis()
-  expect_error(order_cells(cds), "No dimensionality reduction for UMAP calculated. Please run reduce_dimensions with reduction_method = UMAP, cluster_cells, and learn_graph before running order_cells." )
+  expect_error(order_cells(cds), "No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP, cluster_cells, and learn_graph before running order_cells." )
   cds <- estimate_size_factors(cds)
   cds <- preprocess_cds(cds, num_dim = 20)
   cds <- reduce_dimension(cds)
@@ -136,7 +136,7 @@ cds <- load_a549()
 set.seed(100)
 test_that("order_cells error messages work", {
   skip_not_travis()
-  expect_error(order_cells(cds), "No dimensionality reduction for UMAP calculated. Please run reduce_dimensions with reduction_method = UMAP, cluster_cells, and learn_graph before running order_cells." )
+  expect_error(order_cells(cds), "No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP, cluster_cells, and learn_graph before running order_cells." )
   cds <- estimate_size_factors(cds)
   cds <- preprocess_cds(cds, num_dim = 20)
   cds <- reduce_dimension(cds)

diff --git a/tests/testthat/test-subset_cells.R b/tests/testthat/test-subset_cells.R
@@ -4,10 +4,10 @@
 #
 # test_that("test subset_along_path error messages work", {
 #   expect_error(cds <- subset_along_path(cds),
-#                "No dimensionality reduction for UMAP calculated. Please run reduce_dimensions with reduction_method = UMAP and partition_cells before running learn_graph.")
+#                "No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP and partition_cells before running learn_graph.")
 #   cds <- preprocess_cds(cds)
 #   expect_error(cds <- subset_along_path(cds),
-#                "No dimensionality reduction for UMAP calculated. Please run reduce_dimensions with reduction_method = UMAP and partition_cells before running learn_graph.")
+#                "No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP and partition_cells before running learn_graph.")
 #   cds <- reduce_dimension(cds)
 #   expect_error(cds <- subset_along_path(cds),
 #                "No cell partition for UMAP calculated. Please run partition_cells with reduction_method = UMAP before running learn_graph.")