0.99.2 update to bioconductor submission

.Rbuildignore

@@ -18,3 +18,6 @@
 ^old\.README\.md$
 ^readme_images$
 ^scenic_bash$
+^vignettes/articles$
+.nojekyll$
+

.github/.gitignore

@@ -0,0 +1 @@
+*.html

.github/copy_to_branch.sh

@@ -1,15 +1,16 @@
 # Designate desired directories and files
-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
+FILES=(
+'data-raw/'*
+'man/'*
+'R/'*
+'tests/'*
+'vignettes/'*
+'DESCRIPTION'
+'NAMESPACE'
+'NEWS.md'
+'README.md'
+'inst/CITATION'
+)
 
 echo "${FILES[@]}"
 
@@ -21,8 +22,9 @@ git fetch
 # Checkout target branch                         
 git checkout $TARGET_BRANCH
 # copy files from the branch the action is being run upon
-SRC_BRANCH=$(git symbolic-ref --short HEAD)
-git checkout $SRC_BRANCH -- $FILES
+for F in ${FILES}; do
+git checkout $SRC_BRANCH -- ${F}
+done
 # 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

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

.github/workflows/pull_request_template.md

@@ -0,0 +1,18 @@
+This is a code review template, it will be displayed after each pull request. 
+We do code reviews because we care about quality of our codebase and because we care about long-term development goals.
+We do not do code reviews to blame the ones who contribute. There is no seniority in this process and there is no perfect code, 
+we just want to avoid storing code that is not OK.
+
+## For the submitter
+
+- [ ] `R CMD build` & `R CMD check` pass
+- [ ] `BiocCheck` passes
+- [ ]  Needed tests exist and passing or not needed
+- [ ]  The change is sufficiently small
+
+## For the reviewer
+
+- [ ] OK, code does what it's intended for
+- [ ] its' OK to do it that way
+- [ ] it's OK to read and comprehend the code
+- [ ] tests, documentation, style are OK

.github/workflows/r-build-check.yml

@@ -1,9 +1,7 @@
 name: r-build-check
 on:
-    push:
-        branches: ['v0.2.2_development']
     pull_request:
-        branches: ['master', 'v0.2.2']
+        branches: ['master', 'dev']
     workflow_dispatch:
 
 jobs:

.gitignore

@@ -10,6 +10,3 @@ R/.Rhistory
 scenic/*
 
 scratch/
-
-.github/workflows/doc_update.yml
-.github/workflows/pkgdown_update.yml

.nojekyll

@@ -0,0 +1 @@
+

DESCRIPTION

@@ -1,6 +1,6 @@
-Package: domino2
+Package: dominoSignal
 Title: Cell Communication Analysis for Single Cell RNA Sequencing
-Version: 0.99.1
+Version: 0.99.2
 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")),
@@ -11,8 +11,8 @@ Authors@R: c(
     person("Jennifer", "Elisseeff", role = "ctb", email = "[email protected]", comment = c(ORCID = "0000-0002-5066-1996"))
     )
 Description: 
-    Domino2 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/domino2/issues
+    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),
 Imports:
@@ -44,7 +44,9 @@ Suggests:
     Seurat,
     testthat,
     formatR,
-    BiocFileCache
+    BiocFileCache,
+    SingleCellExperiment
 VignetteBuilder: knitr
 Language: en-US
 Roxygen: list(markdown = TRUE)
+URL: https://fertiglab.github.io/dominoSignal/

NEWS.md

@@ -1,4 +1,22 @@
-# domino2 v0.2.2
+# dominoSignal v0.99.2
+
+## Package Name
+
+- Update of package name from "domino2" to "dominoSignal"
+
+## Bioconductor Standards
+
+- 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
+- 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
+
+
+# dominoSignal v0.99.1
+
+- Update to Bioconductor version numbering conventions for package submission
+
+# dominoSignal v0.2.2
 
 ## Linkage functions
 - Addition of new class to summarize linkages in objects
@@ -8,7 +26,7 @@
 ## Package structure
 - Adjustments made to meet BioConductor standards
 
-# domino2 v0.2.1
+# 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

R/class_definitions.R

@@ -23,6 +23,7 @@ NULL
 #' @name domino-class
 #' @rdname domino-class
 #' @exportClass domino
+#' @return an instance of class `domino `
 #'
 domino <- methods::setClass(
   Class = "domino",
@@ -58,6 +59,7 @@ domino <- methods::setClass(
 #' @name linkage_summary-class
 #' @rdname linkage_summary-class
 #' @exportClass linkage_summary
+#' @return an instance of class `linkage_summary`
 #'
 linkage_summary <- setClass(
   Class = "linkage_summary",
@@ -76,7 +78,7 @@ linkage_summary <- setClass(
 #' @return a printed description of the number of cell clusters in the object
 #' @keywords internal
 #' @examples
-#' print(domino2:::pbmc_dom_built_tiny)
+#' print(dominoSignal:::pbmc_dom_built_tiny)
 #' 
 setMethod("print", "domino", function(x, ...) {
   if (x@misc$build) {
@@ -103,9 +105,9 @@ setMethod("print", "domino", function(x, ...) {
 #' @return a printed description of the number of cells in a domino object and its build status
 #' @keywords internal
 #' @examples
-#' domino2:::pbmc_dom_built_tiny
+#' dominoSignal:::pbmc_dom_built_tiny
 #' 
-#' show(domino2:::pbmc_dom_built_tiny)
+#' show(dominoSignal:::pbmc_dom_built_tiny)
 #' 
 setMethod("show", "domino", function(object) {
   if (object@misc$build) {

R/convenience_fxns.R

@@ -15,39 +15,64 @@ NULL
 #'
 #' @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.
 #' @return A domino object with clusters renamed in all applicable slots.
-#' @keywords internal
 #' @export
 #' @examples 
 #' new_clust <- c("CD8_T_cell" = "CD8+ T Cells",
 #'  "CD14_monocyte" = "CD14+ Monocytes", "B_cell" = "B Cells")
-#' pbmc_dom_built_tiny <- rename_clusters(domino2:::pbmc_dom_built_tiny, new_clust)
+#' pbmc_dom_built_tiny <- rename_clusters(dominoSignal:::pbmc_dom_built_tiny, new_clust)
 #'
-rename_clusters <- function(dom, clust_conv) {
-  if (is.null(dom@clusters)) {
-    stop("There are no clusters in this domino object")
-  }
-  if (dom@misc$create) {
-    dom@clusters <- revalue(dom@clusters, clust_conv)
-    colnames(dom@clust_de) <- clust_conv
-    names(colnames(dom@clust_de)) <- c()
-    colnames(dom@misc$cl_rec_percent) <- clust_conv
-  }
-  if (dom@misc$build) {
-    names(dom@linkages$clust_tf) <- clust_conv
-    names(dom@linkages$clust_rec) <- clust_conv
-    names(dom@linkages$clust_incoming_lig) <- clust_conv
-    names(dom@linkages$clust_tf_rec) <- clust_conv
-    colnames(dom@signaling) <- paste0("L_", clust_conv)
-    rownames(dom@signaling) <- paste0("R_", clust_conv)
-    names(dom@cl_signaling_matrices) <- clust_conv
-    for (cl in clust_conv) {
-      colnames(dom@cl_signaling_matrices[[cl]]) <- paste0("L_", clust_conv)
+rename_clusters <- function(dom, clust_conv, warning = FALSE) {
+    if (is.null(dom@clusters)) {
+        stop("There are no clusters in this domino object")
     }
-  }
-  return(dom)
+    if (dom@misc$create) {
+        dom@clusters <- plyr::revalue(dom@clusters, clust_conv, warn_missing = warning)
+        colnames(dom@clust_de) <- plyr::revalue(colnames(dom@clust_de), clust_conv, warn_missing = warning)
+        names(colnames(dom@clust_de)) <- c()
+        colnames(dom@misc$cl_rec_percent) <- plyr::revalue(colnames(dom@misc$cl_rec_percent),
+            clust_conv,
+            warn_missing = warning
+        )
+    }
+    if (dom@misc$build) {
+        names(dom@linkages$clust_tf) <- plyr::revalue(names(dom@linkages$clust_tf), clust_conv, warn_missing = warning)
+        names(dom@linkages$clust_rec) <- plyr::revalue(names(dom@linkages$clust_rec), clust_conv, warn_missing = warning)
+        names(dom@linkages$clust_incoming_lig) <- plyr::revalue(names(dom@linkages$clust_incoming_lig),
+            clust_conv,
+            warn_missing = warning
+        )
+        names(dom@linkages$clust_tf_rec) <- plyr::revalue(names(dom@linkages$clust_tf_rec),
+            clust_conv,
+            warn_missing = warning
+        )
+        sig_ligands <- colnames(dom@signaling)
+        sig_rec <- rownames(dom@signaling)
+        # Remove L_ prefix
+        sig_ligand_clust <- gsub("^L_", "", sig_ligands)
+        # Remove R_ prefix
+        sig_rec_clust <- gsub("^R_", "", sig_rec)
+        new_lig_clust <- plyr::revalue(sig_ligand_clust, clust_conv, warn_missing = warning)
+        new_rec_clust <- plyr::revalue(sig_rec_clust, clust_conv, warn_missing = warning)
+        colnames(dom@signaling) <- paste0("L_", new_lig_clust)
+        rownames(dom@signaling) <- paste0("R_", new_rec_clust)
+        names(dom@cl_signaling_matrices) <- plyr::revalue(names(dom@cl_signaling_matrices),
+            clust_conv,
+            warn_missing = warning
+        )
+        for (cl in names(dom@cl_signaling_matrices)) {
+            cl_sig_ligands <- colnames(dom@cl_signaling_matrices[[cl]])
+            # Remove L_ prefix
+            cl_sig_lig_clust <- gsub("^L_", "", cl_sig_ligands)
+            cl_sig_lig_new <- plyr::revalue(cl_sig_lig_clust, clust_conv, warn_missing = warning)
+            colnames(dom@cl_signaling_matrices[[cl]]) <- paste0("L_", cl_sig_lig_new)
+        }
+    }
+    return(dom)
 }
 
+
 #' Convert Genes Using Table
 #'
 #' Takes a vector of gene inputs and a conversion table  and returns a