docs: update documentation links and examples for clarity and consistency across multiple plot functions

Author: pwwang

R/celldimplot.R

@@ -38,7 +38,7 @@
 #'         (`lineages`).
 #'   \item **Velocity arrows** — Overlay RNA velocity vectors on the embedding
 #'         (`velocity`). For dedicated velocity visualization with grid or
-#'         stream plots, see [CellVelocityPlot()].
+#'         stream plots, see \code{\link{CellVelocityPlot}}.
 #'   \item **Statistical charts** — Embed small bar, ring, or line charts at
 #'         group positions showing composition of a second variable (`stat_by`,
 #'         `stat_plot_type`).
@@ -78,7 +78,7 @@
 #' reduction plot. The `velocity` parameter names a second reduction
 #' (e.g., `"stochastic_UMAP"`) whose first two dimensions encode the velocity
 #' arrows. This is a lightweight overlay — for dedicated velocity visualization
-#' with grid or stream plots, use [CellVelocityPlot()] which delegates to
+#' with grid or stream plots, use \code{\link{CellVelocityPlot}} which delegates to
 #' \code{\link[plotthis:VelocityPlot]{plotthis::VelocityPlot()}}.
 #'
 #' @param object A Seurat object, a Giotto object, a path to an `.h5ad` file,
@@ -100,7 +100,7 @@
 #'   encode RNA velocity vectors to overlay on the plot. Typical values are
 #'   `"stochastic_<reduction>"`, `"deterministic_<reduction>"`, or
 #'   `"dynamical_<reduction>"` (e.g., `"stochastic_UMAP"`). For dedicated
-#'   velocity visualization (grid or stream plots), use [CellVelocityPlot()]
+#'   velocity visualization (grid or stream plots), use \code{\link{CellVelocityPlot}}
 #'   instead. Default is `NULL` (no velocity overlay).
 #' @param group_by Character vector of metadata column name(s) used to color
 #'   the cells. Can be a single column (e.g., `"CellType"`) or multiple
@@ -169,8 +169,8 @@
 #' \itemize{
 #'   \item \code{\link[plotthis:DimPlot]{plotthis::DimPlot()}} — The
 #'         underlying plotting engine
-#'   \item [CellVelocityPlot()] — Dedicated RNA velocity visualization
-#'   \item [CellStatPlot()] — Statistical summaries and comparisons
+#'   \item \code{\link{CellVelocityPlot}} — Dedicated RNA velocity visualization
+#'   \item \code{\link{CellStatPlot}} — Statistical summaries and comparisons
 #' }
 #'
 #' @export
@@ -573,7 +573,7 @@ CellDimPlot.H5File <- function(
 #' For example, `"stochastic_UMAP"` or `"dynamical_PCA"`.
 #'
 #' @section Relationship to CellDimPlot:
-#' While [CellDimPlot()] can overlay velocity arrows on a dimension reduction
+#' While \code{\link{CellDimPlot}} can overlay velocity arrows on a dimension reduction
 #' plot via its `velocity` parameter, `CellVelocityPlot` is the dedicated
 #' velocity visualization function. The key differences are:
 #' \itemize{
@@ -608,7 +608,7 @@ CellDimPlot.H5File <- function(
 #'   or an opened `H5File` from the \pkg{hdf5r} package.
 #' @param reduction Name of the main dimension reduction that defines cell
 #'   positions in the plot (e.g., `"umap"`, `"pca"`, `"tsne"`). This
-#'   reduction must already exist in the object. Unlike [CellDimPlot()],
+#'   reduction must already exist in the object. Unlike \code{\link{CellDimPlot}},
 #'   this parameter is required — there is no default.
 #' @param v_reduction Name of the velocity reduction that encodes RNA velocity
 #'   vectors (e.g., `"stochastic_UMAP"`, `"dynamical_PCA"`). Only the first
@@ -623,7 +623,7 @@ CellDimPlot.H5File <- function(
 #'   default feature type is auto-detected via
 #'   `GiottoClass::set_default_feat_type()`.
 #' @param group_by Metadata column name used to color cells by group (e.g.,
-#'   `"CellType"`, `"Phase"`). Unlike [CellDimPlot()], this parameter is
+#'   `"CellType"`, `"Phase"`). Unlike \code{\link{CellDimPlot}}, this parameter is
 #'   optional — when `NULL`, all cells are plotted in a uniform color, which
 #'   can be useful for focusing on the velocity flow patterns without visual
 #'   distraction from cluster colors.
@@ -670,9 +670,9 @@ CellDimPlot.H5File <- function(
 #'   \item \code{\link[plotthis:VelocityPlot]{plotthis::VelocityPlot()}} —
 #'         The underlying plotting engine supporting arrow, grid, and stream
 #'         plot types
-#'   \item [CellDimPlot()] — Standard dimension reduction plot; can overlay
+#'   \item \code{\link{CellDimPlot}} — Standard dimension reduction plot; can overlay
 #'         velocity arrows via the `velocity` parameter
-#'   \item [CellStatPlot()] — Statistical summaries and comparisons
+#'   \item \code{\link{CellStatPlot}} — Statistical summaries and comparisons
 #' }
 #'
 #' @export

R/cellstatplot.R

@@ -272,9 +272,9 @@
 #'
 #' @seealso
 #' \itemize{
-#'   \item [CellDimPlot()] — Dimension reduction visualization of
+#'   \item \code{\link{CellDimPlot}} — Dimension reduction visualization of
 #'         cell clusters
-#'   \item [FeatureStatPlot()] — Feature expression statistics
+#'   \item \code{\link{FeatureStatPlot}} — Feature expression statistics
 #'   \item \code{\link[plotthis:BarPlot]{plotthis::BarPlot()}},
 #'         \code{\link[plotthis:Heatmap]{plotthis::Heatmap()}},
 #'         \code{\link[plotthis:SankeyPlot]{plotthis::SankeyPlot()}} —

R/chat.R

@@ -74,6 +74,7 @@
 #' @importFrom rlang %||%
 #' @examples
 #' \donttest{
+#' if (FALSE) {
 #' # Setup LLM provider (requires an API key)
 #' provider <- tidyprompt::llm_provider_openai(
 #'     parameters = list(model = "deepseek-v4-flash", stream = TRUE),
@@ -120,6 +121,7 @@
 #' # Clear history for a fresh conversation
 #' chat$clear_history()
 #' }
+#' }
 SCPlotterChat <- R6::R6Class(
     "SCPlotterChat",
     private = list(

R/clonalstatplot.R

@@ -22,7 +22,7 @@
 #' evaluate within the context of each faceting/splitting group, enabling per-group
 #' selection of the most expanded clones, clones shared between conditions, or clones
 #' meeting custom abundance thresholds. See the \strong{Clone selection} section below
-#' and \code{\link{clone_selectors}} for full details.
+#' and \code{\link{CloneSelectors}} for full details.
 #'
 #' Clones can also be aggregated into named groups (by passing a named list to
 #' \code{clones}), where each group is defined by its own selection expression. In
@@ -49,7 +49,7 @@
 #'       \item \code{gt(g1, g2)}, \code{lt(g1, g2)}, \code{eq(g1, g2)}, etc. — comparison-based selection
 #'     }
 #'     All selectors accept \code{group_by}, \code{top}, \code{order}, \code{within},
-#'     and \code{output_within} arguments. See \code{\link{clone_selectors}} for
+#'     and \code{output_within} arguments. See \code{\link{CloneSelectors}} for
 #'     complete documentation.
 #'   }
 #'   \item{Named list of expressions}{Defines clone groups. Each element is a selection
@@ -231,7 +231,7 @@
 #' }
 #' @seealso
 #' \itemize{
-#'   \item \code{\link{clone_selectors}} for the full clone selection expression system
+#'   \item \code{\link{CloneSelectors}} for the full clone selection expression system
 #'   \item \code{\link{ClonalCompositionPlot}} for visualizing clonal space composition (homeostasis)
 #'   \item \code{\link{ClonalDiversityPlot}} for clonal diversity metrics
 #'   \item \code{\link{ClonalGeneUsagePlot}} for V(D)J gene segment usage
@@ -421,7 +421,7 @@ ClonalStatPlot <- function(
                 error = function(e) {
                     stop(
                         "Invalid clone selector expression: '", clones_expr, "'.\n",
-                        "See ?clone_selectors for available selector functions.\n",
+                        "See ?CloneSelectors for available selector functions.\n",
                         "Parse error: ", e$message,
                         call. = FALSE
                     )

R/spatialplot.R

@@ -1053,16 +1053,6 @@ SpatPlot.giotto <- function(
 #' \code{\link[plotthis:SpatImagePlot]{plotthis::SpatImagePlot()}},
 #' \code{\link[plotthis:SpatShapesPlot]{plotthis::SpatShapesPlot()}}
 #' @export
-#' @examples
-#' \donttest{
-#' # Feature plot on Visium data
-#' data(stxBrain, package = "SeuratData")
-#' SpatFeaturePlot(stxBrain, features = c("Hpca", "Ttr"))
-#'
-#' # Feature plot with image and shapes on FOV data
-#' data(xenium_sub, package = "scplotter")
-#' SpatFeaturePlot(xenium_sub, features = c("Bace2", "Gad1", "Nrg1"))
-#' }
 SpatFeaturePlot <- function(
     object, fov = NULL, boundaries = NULL, image = NULL, masks = NULL, shapes = NULL, points = NULL,
     ext = NULL, crop = TRUE, group_by = NULL, features = NULL, layer = NULL, scale_factor = NULL,
@@ -1207,14 +1197,6 @@ SpatFeaturePlot.giotto <- function(
 #' \code{\link[Seurat:SpatialDimPlot]{Seurat::SpatialDimPlot()}},
 #' \code{\link[Seurat:ImageDimPlot]{Seurat::ImageDimPlot()}}
 #' @export
-#' @examples
-#' \donttest{
-#' data(stxBrain, package = "SeuratData")
-#' SpatDimPlot(stxBrain, group_by = "seurat_clusters")
-#'
-#' data(xenium_sub, package = "scplotter")
-#' SpatDimPlot(xenium_sub, group_by = "cell_type")
-#' }
 SpatDimPlot <- function(
     object, fov = NULL, boundaries = NULL, image = NULL, masks = NULL, shapes = NULL, points = NULL,
     ext = NULL, crop = TRUE, group_by = NULL, features = NULL, layer = NULL, scale_factor = NULL,