Dev

.github/copy_to_branch.sh

@@ -1,16 +1,15 @@
 # Designate desired directories and files
-FILES=(
-'data-raw/'*
-'man/'*
-'R/'*
-'tests/'*
-'vignettes/'*
-'DESCRIPTION'
-'NAMESPACE'
-'NEWS.md'
-'README.md'
-'inst/CITATION'
-)
+SRC_FOLDER_PATHS=(data-raw man R tests vignettes)
+SRC_FILE_PATHS=(DESCRIPTION LICENSE NAMESPACE NEWS.md README.md inst/CITATION)
+
+# Get files from directories
+FILES=$(find "${SRC_FOLDER_PATHS[@]}" -type f)
+
+# Add indicated individual files
+for F in "${SRC_FILE_PATHS[@]}"
+do
+FILES+=" ${F}"
+done
 
 echo "${FILES[@]}"
 
@@ -22,9 +21,8 @@ git fetch
 # Checkout target branch                         
 git checkout $TARGET_BRANCH
 # copy files from the branch the action is being run upon
-for F in ${FILES}; do
-git checkout $SRC_BRANCH -- ${F}
-done
+SRC_BRANCH=$(git symbolic-ref --short HEAD)
+git checkout $SRC_BRANCH -- $FILES
 # Commit to the repository (ignore if no changes)
 git add -A
 git diff-index --quiet HEAD ||  git commit -am "update files"

.github/workflows/bioc_branch.yml

@@ -17,7 +17,6 @@ jobs:
       - uses: actions/checkout@v2
       - name: copy
         env:
-          SRC_BRANCH: 'master'
-          TARGET_BRANCH: 'bioconductor'
+          TARGET_BRANCH: 'master'
         run: .github/copy_to_branch.sh
         shell: bash

.github/workflows/pkgdown.yaml

@@ -22,7 +22,7 @@ jobs:
     permissions:
       contents: write
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
 
       - uses: r-lib/actions/setup-pandoc@v2
 
@@ -41,7 +41,7 @@ jobs:
 
       - name: Deploy to GitHub pages 🚀
         if: github.event_name != 'pull_request'
-        uses: JamesIves/github-pages-deploy-action@v4.4.1
+        uses: JamesIves/github-pages-deploy-action@v4.5.0
         with:
           clean: false
           branch: gh-pages

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: dominoSignal
 Title: Cell Communication Analysis for Single Cell RNA Sequencing
-Version: 0.99.2
+Version: 0.99.3
 Authors@R: c(
     person("Christopher", "Cherry", role = c("aut"), email = "[email protected]", comment = c(ORCID = "0000-0002-5481-0055")),
     person("Jacob T", "Mitchell", role = c("aut", "cre"), email = "[email protected]", comment = c(ORCID = "0000-0002-5370-9692")),
@@ -11,7 +11,7 @@ Authors@R: c(
     person("Jennifer", "Elisseeff", role = "ctb", email = "[email protected]", comment = c(ORCID = "0000-0002-5066-1996"))
     )
 Description: 
-    dominoSignal is a package developed to analyze cell signaling through ligand - receptor - transcription factor networks in scRNAseq data. It takes as input information transcriptomic data, requiring counts, z-scored counts, and cluster labels, as well as information on transcription factor activation (such as from SCENIC) and a database of ligand and receptor pairings (such as from cellphoneDB). This package creates an object storing ligand - receptor - transcription factor linkages by cluster and provides several methods for exploring, summarizing, and visualizing the analysis.
+    dominoSignal is a package developed to analyze cell signaling through ligand - receptor - transcription factor networks in scRNAseq data. It takes as input information transcriptomic data, requiring counts, z-scored counts, and cluster labels, as well as information on transcription factor activation (such as from SCENIC) and a database of ligand and receptor pairings (such as from CellPhoneDB). This package creates an object storing ligand - receptor - transcription factor linkages by cluster and provides several methods for exploring, summarizing, and visualizing the analysis.
 BugReports: https://github.com/FertigLab/dominoSignal/issues
 Depends:
     R(>= 4.2.0),
@@ -31,7 +31,7 @@ Imports:
 License: GPL-3 | file LICENSE
 Encoding: UTF-8
 LazyData: false
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2
 biocViews:
     SystemsBiology,
     SingleCell,

NAMESPACE

@@ -24,6 +24,7 @@ export(feat_heatmap)
 export(gene_network)
 export(incoming_signaling_heatmap)
 export(mean_ligand_expression)
+export(mock_linkage_summary)
 export(plot_differential_linkages)
 export(rename_clusters)
 export(signaling_heatmap)
@@ -32,6 +33,8 @@ export(summarize_linkages)
 export(test_differential_linkages)
 exportClasses(domino)
 exportClasses(linkage_summary)
+exportMethods(print)
+exportMethods(show)
 import(ComplexHeatmap)
 import(biomaRt)
 import(circlize)

NEWS.md

@@ -1,3 +1,25 @@
+# dominoSignal v0.99.3
+
+## create_domino Function Warnings
+
+- Disabled exact p-value computation for the correlation test between receptor expression and features to prevent repeated warning messages due to tied ranks during Spearman correlation calculation 
+
+## Vignettes
+
+- Updated non-functional links to functional URLs
+- All vignettes explicitly state the seed used when executing their code
+- The dominoSignal Object vignette states the purpose of the code used to download and import data from a BioFileCache to demonstrate applications of the domino objects on a real data object that is too large to include inside the package
+
+## Testing Data
+
+- Data used for examples and unit tests is now stored in the package's data/ directory.
+- All usage of the triple colon operator to access internal data from sysdata have been replaced with usage of data()
+- Linkage summaries for demonstrating differential linkage testing and plotting are generated within unit test scripts rather than being stored within the package.
+- Examples are run with echo = FALSE to cut down on lines of code printed in example pages.
+- Examples for create_domino are run with verbose = FALSE
+- Fixed example of changing colors for circos_ligand_receptor
+- Fixed example of boolean representation of cor_heatmap
+
 # dominoSignal v0.99.2
 
 ## Package Name
@@ -6,9 +28,9 @@
 
 ## Bioconductor Standards
 
-- Update to Vignettes presenting application of the DominoSignal pipeline on data formatted as a SingleCellExperiment object
+- Update to vignettes presenting application of the DominoSignal pipeline on data formatted as a SingleCellExperiment object
 - Implemented caching of example data by BiocCache to meet package size limits
-- Removal of depreciated scripts for running SCENIC. Tutorials for running SCENIC are still present in vignettes
+- Removal of deprecated scripts for running SCENIC. Tutorials for running SCENIC are still present in vignettes
 - Corrected BiocCheck notes pertaining to coding practices including paste in conditional statements, functions with dontrun examples, usage of seq_len or seq_along in place of seq, and usage of vapply in place of sapply
 
 
@@ -24,17 +46,17 @@
 - Plotting function for differential linkages
 
 ## Package structure
-- Adjustments made to meet BioConductor standards
+- Adjustments made to meet Bioconductor standards
 
 # dominoSignal v0.2.1
 
 ## Updates to domino object construction
-- Uniform formats for inputs of receptor-ligand interaction databases, transcription factor activity features, and regulon gene lists for operability with alternative databases and transcription factor activation inference methods
+- Uniform formats for inputs of receptor - ligand interaction databases, transcription factor activity features, and regulon gene lists for operability with alternative databases and transcription factor activation inference methods
 - Helper functions for reformatting pySCENIC outputs and CellPhoneDB database files to domino-readable uniform formats
 - Assessment of transcription factor linkage with receptors that function as a heteromeric complex based on correlation between transcription factor activity and all receptor component genes
 - Assessment of complex ligand expression as the mean of component gene expression for plotting functions
 - Minimum threshold for the percentage of cells in a cluster expressing a receptor gene for the receptor to be called active within the cluster
-- Additional linkage slots for active receptors in each cluster, transcription factor-receptor linkages for each cluster, and incoming ligands for active receptors on each cluster
+- Additional linkage slots for active receptors in each cluster, transcription factor - receptor linkages for each cluster, and incoming ligands for active receptors on each cluster
 
 ## Plotting functions
 - Chord plot of ligand expression targeting a specified receptor where chord widths correspond to the quantity of ligand expression by each cell cluster
@@ -43,7 +65,7 @@
 
 ## Bugfixes
 - Added host option for gene ortholog conversions using `{biomaRt}` for access to maintained mirrors
-- Transcription factor-target linkages are now properly stored so that receptors in a transcription factor's regulon are excluded from linkage
+- Transcription factor - target linkages are now properly stored so that receptors in a transcription factor's regulon are excluded from linkage
 - Ligand nodes sizes in gene networks correspond to quantity of ligand expression
 - `create_domino()` can be run without providing a regulon list
 - References to the host GitHub repository have been updated to [Elisseeff-Lab](https://github.com/Elisseeff-Lab/domino)

R/class_definitions.R

@@ -2,18 +2,18 @@
 #' @importClassesFrom Matrix dgCMatrix
 #'
 NULL
-#' The domino Class
+#' The domino class
 #'
 #' The domino class contains all information necessary to calculate receptor-ligand
 #' signaling. It contains z-scored expression, cell cluster labels, feature values,
 #' and a referenced receptor-ligand database formatted as a receptor-ligand map.
 #' Calculated intermediate values are also stored.
 #'
-#' @slot db_info List of data sets from lr database.
+#' @slot db_info List of data sets from ligand - receptor database
 #' @slot counts Raw count gene expression data
 #' @slot z_scores Matrix of z-scored expression data with cells as columns
 #' @slot clusters Named factor with cluster identity of each cell
-#' @slot features Matrix of features to correlate receptor-ligand expression with. Cells are columns and features are rows.
+#' @slot features Matrix of features (TFs) to correlate receptor - ligand expression with. Cells are columns and features are rows.
 #' @slot cor Correlation matrix of receptor expression to features.
 #' @slot linkages List of lists containing info linking cluster->tf->rec->lig
 #' @slot clust_de Data frame containing differential expression results for features by cluster.
@@ -23,7 +23,7 @@ NULL
 #' @name domino-class
 #' @rdname domino-class
 #' @exportClass domino
-#' @return an instance of class `domino `
+#' @return An instance of class `domino `
 #'
 domino <- methods::setClass(
   Class = "domino",
@@ -74,22 +74,24 @@ linkage_summary <- setClass(
 #'
 #' Prints a summary of a domino object
 #'
-#' @param x Domino object
-#' @return a printed description of the number of cell clusters in the object
-#' @keywords internal
+#' @param x A domino object
+#' @param ... Additional arguments to be passed to other methods
+#' @return A printed description of the number of cells and clusters in the domino object
+#' @export
 #' @examples
-#' print(dominoSignal:::pbmc_dom_built_tiny)
-#' 
+#' example(build_domino, echo = FALSE)
+#' print(pbmc_dom_built_tiny)
+#'
 setMethod("print", "domino", function(x, ...) {
   if (x@misc$build) {
     message(
       "A domino object of ", length(x@clusters), " cells
-                Contains signaling between",
-      length(levels(x@clusters)), "clusters
-                Built with a maximum of", as.integer(x@misc$build_vars["max_tf_per_clust"]),
-      "TFs per cluster
-                and a maximum of", as.integer(x@misc$build_vars["max_rec_per_tf"]),
-      "receptors per TF\n"
+                Contains signaling between ",
+      length(levels(x@clusters)), " clusters
+                Built with a maximum of ", x@misc$build_vars["max_tf_per_clust"],
+      " TFs per cluster
+                and a maximum of ", x@misc$build_vars["max_rec_per_tf"],
+      " receptors per TF\n"
     )
   } else {
     message(c("A domino object of ", length(x@clusters), " cells\n", "A signaling network has not been built\n"),
@@ -101,13 +103,12 @@ setMethod("print", "domino", function(x, ...) {
 #'
 #' Shows content overview of domino object
 #'
-#' @param object Domino object
-#' @return a printed description of the number of cells in a domino object and its build status
-#' @keywords internal
+#' @param object A domino object
+#' @return A printed description of cell numbers and clusters in the object
+#' @export
 #' @examples
-#' dominoSignal:::pbmc_dom_built_tiny
-#' 
-#' show(dominoSignal:::pbmc_dom_built_tiny)
+#' example(build_domino, echo = FALSE)
+#' show(pbmc_dom_built_tiny)
 #' 
 setMethod("show", "domino", function(object) {
   if (object@misc$build) {

R/convenience_fxns.R

@@ -5,23 +5,18 @@ NULL
 
 #' Renames clusters in a domino object
 #'
-#' This function reads in a receptor ligand signaling database, cell level
-#' features of some kind (ie. output from pySCENIC), z-scored single cell data,
-#' and cluster id for single cell data, calculates a correlation matrix between
-#' receptors and other features (this is transcription factor module scores if
-#' using pySCENIC), and finds features enriched by cluster. It will return a
-#' domino object prepared for [build_domino()], which will calculate a signaling
-#' network.
+#' This function renames the clusters used to build a domino object
 #'
-#' @param dom Domino object to rename clusters in
-#' @param clust_conv Named vector of conversions from old to new clusters. Values are taken as new clusters IDs and names as old cluster IDs.
-#' @param warning Logical. If TRUE, will warn if a cluster is not found in the conversion table. Default is FALSE.
+#' @param dom a domino object to rename clusters in
+#' @param clust_conv named vector of conversions from old to new clusters. Values are taken as new clusters IDs and names as old cluster IDs.
+#' @param warning logical. If TRUE, will warn if a cluster is not found in the conversion table. Default is FALSE.
 #' @return A domino object with clusters renamed in all applicable slots.
 #' @export
 #' @examples 
+#' example(build_domino, echo = FALSE)
 #' new_clust <- c("CD8_T_cell" = "CD8+ T Cells",
 #'  "CD14_monocyte" = "CD14+ Monocytes", "B_cell" = "B Cells")
-#' pbmc_dom_built_tiny <- rename_clusters(dominoSignal:::pbmc_dom_built_tiny, new_clust)
+#' pbmc_dom_built_tiny <- rename_clusters(pbmc_dom_built_tiny, new_clust)
 #'
 rename_clusters <- function(dom, clust_conv, warning = FALSE) {
     if (is.null(dom@clusters)) {
@@ -73,17 +68,17 @@ rename_clusters <- function(dom, clust_conv, warning = FALSE) {
 }
 
 
-#' Convert Genes Using Table
+#' Convert genes using a table
 #'
-#' Takes a vector of gene inputs and a conversion table  and returns a 
+#' Takes a vector of gene inputs and a conversion table and returns a
 #' converted gene table
 #'
-#' @param genes The genes to convert.
-#' @param from  Gene symbol type of the input (ENSG, ENSMUSG, HGNC, MGI)
-#' @param to    Desired gene symbol type for the output (HGNC, MGI)
-#' @param conversion_table A data.frame with column names corresponding to gene symbol types (mm.ens, hs.ens, mgi, hgnc)
+#' @param genes the genes to convert
+#' @param from  gene symbol type of the input (ENSG, ENSMUSG, HGNC, MGI)
+#' @param to    desired gene symbol type for the output (HGNC, MGI)
+#' @param conversion_table a data frame with column names corresponding to gene symbol types (mm.ens, hs.ens, mgi, hgnc)
 #' and rows corresponding to the gene symbols themselves
-#' @return Data frame of genes with original and corresponding converted symbols
+#' @return A data frame of genes with original and corresponding converted symbols
 #' @keywords internal
 #'
 table_convert_genes <- function(genes, from, to, conversion_table) {

R/data.R

@@ -0,0 +1,47 @@
+#' SCENIC AUC subset
+#'
+#' A subset of SCENIC AUCs as applied to PBMC data.
+#'
+#' @format A list of:
+#' \describe{
+#'  \item{auc_tiny}{A subset of SCENIC AUCs}
+#'  \item{regulons_tiny}{A subset of SCENIC regulons}
+#' }
+#'
+#' @source <https://zenodo.org/records/10951634/files>
+#' @usage data("SCENIC")
+"SCENIC"
+
+
+#' PBMC RNAseq data subset
+#'
+#' A subset of the results of PBMC RNA-seq data.
+#'
+#' @format A list of::
+#' \describe{
+#'  \item{RNA_count_tiny}{A subset of PBMC RNA-seq data: counts assay}
+#'  \item{RNA_zscore_tiny}{A subset of PBMC RNA-seq data: zscore assay}
+#'  \item{clusters_tiny}{A subset of PBMC RNA-seq data: clusters as defined by cell_type}
+#' }
+#'
+#' @source <https://zenodo.org/records/10951634/files/pbmc3k_sce.rds>
+#' @usage data("PBMC")
+"PBMC"
+
+
+#' CellPhoneDB subset
+#'
+#' A list of four subsets of CellPhoneDB data.
+#'
+#'
+#' @format A list of:
+#' \describe{
+#'  \item{genes_tiny}{A subet of CellPhoneDB gene_input.csv}
+#'  \item{proteins_tiny}{A subset of CellPhoneDB protein_input.csv}
+#'  \item{complexes_tiny}{A subset of CellPhoneDB complex_input.csv}
+#'  \item{interactions_tiny}{A subset of CellPhoneDB interaction_input.csv}
+#' }
+#' 
+#' @source <https://github.com/ventolab/cellphonedb-data/archive/refs/tags/v4.0.0.tar.gz>
+#' @usage data("CellPhoneDB")
+"CellPhoneDB"