docs: add CCCPlot and ClonalX plots to README and mention scRepertoir…

…e in the Credits in README

NAMESPACE

@@ -86,11 +86,13 @@ importFrom(plotthis,LollipopPlot)
 importFrom(plotthis,Network)
 importFrom(plotthis,PieChart)
 importFrom(plotthis,PrepareEnrichrResult)
+importFrom(plotthis,RadarPlot)
 importFrom(plotthis,RarefactionPlot)
 importFrom(plotthis,RidgePlot)
 importFrom(plotthis,RingPlot)
 importFrom(plotthis,SankeyPlot)
 importFrom(plotthis,ScatterPlot)
+importFrom(plotthis,SpiderPlot)
 importFrom(plotthis,TrendPlot)
 importFrom(plotthis,UpsetPlot)
 importFrom(plotthis,VennDiagram)

R/cccplot.R

@@ -1,9 +1,10 @@
 #' Cell-Cell Communication Plot
 #'
 #' @description Plot the cell-cell communication.
-#'  See also the review: https://www.sciencedirect.com/science/article/pii/S2452310021000081
-#'  the LIANA package: https://liana-py.readthedocs.io/en/latest/notebooks/basic_usage.html#Tileplot
-#'  and the CCPlotR package: https://github.com/Sarah145/CCPlotR
+#'  See also:
+#'  * The review: \url{https://www.sciencedirect.com/science/article/pii/S2452310021000081}
+#'  * The LIANA package: \url{https://liana-py.readthedocs.io/en/latest/notebooks/basic_usage.html#Tileplot}
+#'  * The CCPlotR package: \url{https://github.com/Sarah145/CCPlotR}
 #'
 #' @param data A data frame with the cell-cell communication data.
 #'  A typical data frame should have the following columns:
@@ -28,6 +29,11 @@
 #'  * sankey: A sankey plot with the source and target cells as the nodes and the communication as the flows.
 #'  * alluvial: Alias of "sankey".
 #'  * dot: A dot plot with the source and target cells as the nodes and the communication as the dots.
+#' @param method The method to determine the plot entities.
+#'  * aggregation: Aggregate the ligand-receptor pairs interactions for each source-target pair.
+#'    Only the source / target pairs will be plotted.
+#'  * interaction: Plot the ligand-receptor pairs interactions directly.
+#'    The ligand-receptor pairs will also be plotted.
 #' @param magnitude The column name in the data to use as the magnitude of the communication.
 #'  By default, the second last column will be used.
 #'  See `li.mt.show_methods()` for the available methods in `LIANA`.
@@ -71,8 +77,10 @@
 #' @examples
 #' set.seed(8525)
 #' data(cellphonedb_res)
-#' CCCPlot(data = cellphonedb_res)
+#' CCCPlot(data = cellphonedb_res, plot_type = "network", legend.position = "none",
+#'  theme = "theme_blank", theme_args = list(add_coord = FALSE))
 #' CCCPlot(cellphonedb_res, plot_type = "chord")
+#' CCCPlot(cellphonedb_res, plot_type = "heatmap")
 #' CCCPlot(cellphonedb_res, plot_type = "dot", weighted = FALSE)
 #'
 #' cellphonedb_res_sub <- cellphonedb_res[
@@ -158,7 +166,7 @@ CCCPlot <- function(
         if (plot_type == "network") {
             Network(links, from = source_col, to = target_col, node_fill_by = "name",
                 link_curvature = link_curvature, link_weight_name = link_weight_name, link_alpha = link_alpha,
-                node_fill_name = "Entities", link_weight_by = "interactionStrength", ...)
+                node_fill_name = "Source/Target", link_weight_by = "interactionStrength", ...)
         } else if (plot_type %in% c("chord", "circos")) {
             ChordPlot(links, y = "interactionStrength", from = source_col, to = target_col,
                 ...)
@@ -204,7 +212,7 @@ CCCPlot <- function(
         } else if (plot_type == "heatmap") {
             data$ligand_receptor <- paste0(data[[ligand_col]], " -> ", data[[receptor_col]])
             all_lrs <- unique(data$ligand_receptor)
-            data <- pivot_wider(data, names_from = ligand_receptor, values_from = magnitude,
+            data <- pivot_wider(data, names_from = "ligand_receptor", values_from = magnitude,
                 values_fill = 0)
             Heatmap(data, rows = all_lrs, rows_name = "Ligand -> Receptor",
                 name = magnitude, columns_by = target_col, columns_split_by = source_col,

README.md

@@ -14,10 +14,12 @@ $ conda install pwwang::r-scplotter
 
 ## Credits
 
-`scplotter` is greatly inspired by the [`SCP`][2] package, where the visualization was detached from the analysis and implemented in the [`plotthis`][1] package. The `scplotter` package is built upon the `plotthis` package and provides a set of even higher-level functions to visualize single-cell sequencing data.
+`scplotter` draws significant inspiration from the [`SCP`][2] package, which separates visualization from analysis and implements it in the [`plotthis`][1] package. Building on `plotthis`, `scplotter` offers advanced functions for visualizing single-cell sequencing data. Special thanks to the [`scRepertoire`][2] package for its APIs that facilitate the analysis of single-cell TCR/BCR sequencing data.
 
 ## Gallery
 
+### scRNA-seq
+
 [`CellDimPlot`][3]
 
 ![CellDimPlot](./man/figures/celldimplot.png)
@@ -46,6 +48,20 @@ $ conda install pwwang::r-scplotter
 
 ![VolcanoPlot](./man/figures/volcanoplot.png)
 
+[`CCCPlot`][10]
+
+![CCCPlot](./man/figures/cccplot.png)
+
+### scTCR-seq/scBCR-seq
+
+[`ClonalVolumePlot`][11] | [`ClonalAbundancePlot`][12] | [`ClonalResidencyPlot`][13] | [`ClonalCompositionPlot`][14] | [`ClonalOverlapPlot`][15] | [`ClonalGeneUsagePlot`][16]
+
+![clonalstat](./man/figures/clonalstat.png)
+
+[`ClonalRarefactionPlot`][17] | [`ClonalGeneUsagePlot`][18] | [`ClonalDiversityPlot`][19] | [`ClonalPositionalPlot`][20]
+
+![clonaldiv](./man/figures/clonaldiv.png)
+
 [1]: https://github.com/pwwang/plotthis
 [2]: https://zhanghao-njmu.github.io/SCP/index.html
 [3]: https://pwwang.github.io/scplotter/reference/CellDimPlot.html
@@ -55,3 +71,14 @@ $ conda install pwwang::r-scplotter
 [7]: https://pwwang.github.io/scplotter/reference/EnrichmentPlot.html
 [8]: https://pwwang.github.io/plotthis/reference/gsea.html
 [9]: https://pwwang.github.io/plotthis/reference/VolcanoPlot.html
+[10]: https://pwwang.github.io/plotthis/reference/CCCPlot.html
+[11]: https://pwwang.github.io/scplotter/reference/ClonalVolumePlot.html
+[12]: https://pwwang.github.io/scplotter/reference/ClonalAbundancePlot.html
+[13]: https://pwwang.github.io/scplotter/reference/ClonalResidencyPlot.html
+[14]: https://pwwang.github.io/scplotter/reference/ClonalCompositionPlot.html
+[15]: https://pwwang.github.io/scplotter/reference/ClonalOverlapPlot.html
+[16]: https://pwwang.github.io/scplotter/reference/ClonalGeneUsagePlot.html
+[17]: https://pwwang.github.io/scplotter/reference/ClonalRarefactionPlot.html
+[18]: https://pwwang.github.io/scplotter/reference/ClonalGeneUsagePlot.html
+[19]: https://pwwang.github.io/scplotter/reference/ClonalDiversityPlot.html
+[20]: https://pwwang.github.io/scplotter/reference/ClonalPositionalPlot.html

_pkgdown.yml

@@ -11,6 +11,7 @@ reference:
     - ClustreePlot
     - EnrichmentPlot
     - FeatureStatPlot
+    - CCCPlot
   - title: scTCR-seq/scBCR-seq
     desc: Functions for plotting single cell TCR-seq/BCR-seq data
     contents:
@@ -30,6 +31,7 @@ reference:
     contents:
     - ifnb_sub
     - pancreas_sub
+    - cellphonedb_res
   - title: Re-exports
     desc: Functions that are re-exported from plotthis
     contents: