From bf4c12f41c45561bcc2010b5123f0c2c322265c8 Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Thu, 5 May 2022 14:26:17 +0200
Subject: [PATCH 01/17] Create createPPI_OmniPath.R

---
 R/createPPI_OmniPath.R | 51 ++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 51 insertions(+)
 create mode 100644 R/createPPI_OmniPath.R

diff --git a/R/createPPI_OmniPath.R b/R/createPPI_OmniPath.R
new file mode 100644
index 0000000..f80842a
--- /dev/null
+++ b/R/createPPI_OmniPath.R
@@ -0,0 +1,51 @@
+#' Create protein-protein interactions.
+#'
+#' Create a protein-protein interaction network for the reconstruction of cell
+#' signaling pathways.
+#'
+#' @param filename character; protein interaction data.
+#' @param expr dgCMatrix; gene expression in each cell, found in
+#' CellRouter@@ndata.
+#'
+#' @return list; the network (igraph object), the ctable (data frame) with the
+#' edge list, the table (data frame) with the information of the ids of gene A
+#' and B and the scores, the genes in total (character vector), genesPPI
+#' (character vector) with the genes in the interactions, and the remove
+#' (character vector) with the genes not used in the interactions.
+#'
+#' @export
+createPPI <- function(filename, expr){
+  a <- expr
+  data = read.csv(filename, sep='\t', header=FALSE)
+  cat(dim(data))
+  cat('\nProtein interaction data loaded!')
+  # The columns names are usually fixed.
+  ppi <- data[, c('V5','V6', 'V15')] #geneA and geneB, score
+  ppi <- as.data.frame(apply(ppi, 2, function(x)gsub('\\s+', '',x)))
+  geneA <- as.vector(unlist(lapply(strsplit(as.character(ppi[,'V5']),
+                                            split="\\:"), "[", 2)))
+  geneB <- as.vector(unlist(lapply(strsplit(as.character(ppi[,'V6']),
+                                            split="\\:"), "[", 2)))
+  score <- as.vector(unlist(lapply(strsplit(as.character(ppi[,'V15']),
+                                            split="\\:"), "[", 2)))
+  score <- as.numeric(score)
+  geneA <- as.vector(unlist(lapply(strsplit(as.character(geneA),
+                                            split="\\|"), "[", 1)))
+  geneB <- as.vector(unlist(lapply(strsplit(as.character(geneB),
+                                            split="\\|"), "[", 1)))
+  idmap <- data.frame(idA=geneA, idB=geneB, score=score)
+  allgenes <- unique(c(as.vector(idmap$idA), as.vector(idmap$idB)))
+  inetwork <- igraph::graph.data.frame(idmap, directed=FALSE);
+  inetwork <- igraph::simplify(inetwork, remove.multiple = TRUE,
+                               remove.loops = TRUE)
+  genesPPI <- intersect(rownames(expr), allgenes)
+  remove <- setdiff(igraph::V(inetwork)$name, rownames(expr))
+  inetwork <- igraph::delete.vertices(inetwork, remove)
+  ctable <- as.data.frame(igraph::get.edgelist(inetwork))
+  colnames(ctable) <- c('from', 'to')
+  names <- paste(as.vector(ctable$from), as.vector(ctable$to), sep="_")
+  rownames(ctable) <- names
+  network <- list(network=inetwork, ctable=ctable, table=idmap, genes=allgenes,
+                  genesPPI=genesPPI, removed=remove)
+  return(network)
+}

From e5b04c0ea9c3b1bb903af6db69638d44872f5f05 Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Thu, 5 May 2022 14:36:35 +0200
Subject: [PATCH 02/17] Update DESCRIPTION

---
 DESCRIPTION | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 20f4e32..af1876d 100755
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -50,7 +50,8 @@ Imports:
     gridExtra,
     Rcpp,
     RcppEigen,
-    sparseMatrixStats
+    sparseMatrixStats,
+    OmnipathR
 SystemRequirements: Java JDK Oracle 1.8
 RoxygenNote: 7.1.2
 Collate: 

From 8fffcf44f811b6884d23c66f681c3d6646af4b71 Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Thu, 5 May 2022 14:44:12 +0200
Subject: [PATCH 03/17] Update createPPI_OmniPath.R

---
 R/createPPI_OmniPath.R | 31 ++++++++++++++-----------------
 1 file changed, 14 insertions(+), 17 deletions(-)

diff --git a/R/createPPI_OmniPath.R b/R/createPPI_OmniPath.R
index f80842a..f9368f5 100644
--- a/R/createPPI_OmniPath.R
+++ b/R/createPPI_OmniPath.R
@@ -14,26 +14,23 @@
 #' (character vector) with the genes not used in the interactions.
 #'
 #' @export
-createPPI <- function(filename, expr){
+createPPI <- function(expr, species){
   a <- expr
-  data = read.csv(filename, sep='\t', header=FALSE)
-  cat(dim(data))
+  if (species = "Hs") {
+    organism <- 9606
+  }
+  else if (species = "Mm") {
+    organism <- 10090
+  }
+  else if (species = "Rn") {
+    organism <- 10116
+  }
+  data <- as.data.frame(import_omnipath_interactions(datasets = 'omnipath', entity_types = 'protein', organism = organism))
+  cat(dim(ppi))
   cat('\nProtein interaction data loaded!')
   # The columns names are usually fixed.
-  ppi <- data[, c('V5','V6', 'V15')] #geneA and geneB, score
-  ppi <- as.data.frame(apply(ppi, 2, function(x)gsub('\\s+', '',x)))
-  geneA <- as.vector(unlist(lapply(strsplit(as.character(ppi[,'V5']),
-                                            split="\\:"), "[", 2)))
-  geneB <- as.vector(unlist(lapply(strsplit(as.character(ppi[,'V6']),
-                                            split="\\:"), "[", 2)))
-  score <- as.vector(unlist(lapply(strsplit(as.character(ppi[,'V15']),
-                                            split="\\:"), "[", 2)))
-  score <- as.numeric(score)
-  geneA <- as.vector(unlist(lapply(strsplit(as.character(geneA),
-                                            split="\\|"), "[", 1)))
-  geneB <- as.vector(unlist(lapply(strsplit(as.character(geneB),
-                                            split="\\|"), "[", 1)))
-  idmap <- data.frame(idA=geneA, idB=geneB, score=score)
+  ppi <- data[, c('source_genesymbol','target_genesymbol', 'curation_effort')] #geneA and geneB, score
+  idmap <- data.frame(idA=ppi$source_genesymbol, idB=ppi$target_genesymbol, score=as.numeric(ppi$curation_effort))
   allgenes <- unique(c(as.vector(idmap$idA), as.vector(idmap$idB)))
   inetwork <- igraph::graph.data.frame(idmap, directed=FALSE);
   inetwork <- igraph::simplify(inetwork, remove.multiple = TRUE,

From 634b28cf628b21ccd2765de0cfad1ccbadd4738b Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Thu, 5 May 2022 15:39:50 +0200
Subject: [PATCH 04/17] Update cellnetworksPPI_CellComm.R

---
 R/cellnetworksPPI_CellComm.R | 40 ++++++++++++++++++------------------
 1 file changed, 20 insertions(+), 20 deletions(-)

diff --git a/R/cellnetworksPPI_CellComm.R b/R/cellnetworksPPI_CellComm.R
index b46bf7d..9135255 100755
--- a/R/cellnetworksPPI_CellComm.R
+++ b/R/cellnetworksPPI_CellComm.R
@@ -116,32 +116,32 @@ cellnetworksPPI2 <- function(ppi, expr, samples, corThr1, corThr2, column,
                                                  weighted = 'correlation')
     cor.m <- igraph::as_data_frame(cor_g, 'edges')
     rownames(cor.m) <- paste(as.vector(cor.m$from), as.vector(cor.m$to), sep='_')
-    #cor_g <- graph_from_adjacency_matrix(cor, mode='undirected')
-    #cor.m <- melt(cor)
-    #network1 <- igraph::graph.data.frame(cor.m, directed=FALSE);
     #overlap of edges
-    #tmp.net <- (cor_g %s% ppi)
     el <- igraph::get.edgelist(ppi)
     rownames(el) <- paste(el[,1], el[,2], sep='_')
     keep <- intersect(rownames(cor.m), rownames(el))
     cor.m2 <- cor.m[keep,]
-    #cor.m2 <- cor.m2[which(cor.m2$value > 0),]
-    #cor.m2 <- cor.m2[which(cor.m2$correlation > 0),]
     cor.m2 <- cor.m2[which(cor.m2$correlation > corThr2),]
-    network <- igraph::graph.data.frame(cor.m2, directed=FALSE);
-    igraph::E(network)$weight  <- as.vector(cor.m2$correlation)
-    network <- igraph::simplify(network, remove.multiple = TRUE,
-                                remove.loops = TRUE)
-    edges <- as.data.frame(igraph::get.edgelist(network))
-    edges$weight <- abs(igraph::E(network)$weight)
-    edges$corr <- igraph::E(network)$weight
-    celltype <- gsub(" ", ".", celltype)
-    filename <- paste(dir.prefix, celltype, '.txt',sep='')
-    write.table(edges, file=filename, sep='\t', row.names=FALSE,
-                col.names = FALSE, quote=FALSE) #input network
-    gc()
-    corTables[[celltype]] <- network
-    gc(verbose=TRUE)
+    if (nrow(cor.m2) == 0) {
+        print(paste0("No correlation found for ", celltype, " cell type."))
+        gc()
+    }
+    else {
+        network <- igraph::graph.data.frame(cor.m2, directed=FALSE);
+        igraph::E(network)$weight  <- as.vector(cor.m2$correlation)
+        network <- igraph::simplify(network, remove.multiple = TRUE,
+                                    remove.loops = TRUE)
+        edges <- as.data.frame(igraph::get.edgelist(network))
+        edges$weight <- abs(igraph::E(network)$weight)
+        edges$corr <- igraph::E(network)$weight
+        celltype <- gsub(" ", ".", celltype)
+        filename <- paste(dir.prefix, celltype, '.txt',sep='')
+        write.table(edges, file=filename, sep='\t', row.names=FALSE,
+                    col.names = FALSE, quote=FALSE) #input network
+        gc()
+        corTables[[celltype]] <- network
+        gc(verbose=TRUE)
+    }
   }
   return(corTables)
 }

From 188c0cb8c1ce610dcf4cea2e2b0d5fc8176dc86a Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Thu, 5 May 2022 15:46:15 +0200
Subject: [PATCH 05/17] Update findpaths.simpleRJava_CellComm.R

---
 R/findpaths.simpleRJava_CellComm.R | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/R/findpaths.simpleRJava_CellComm.R b/R/findpaths.simpleRJava_CellComm.R
index 093e7c1..4de85ae 100755
--- a/R/findpaths.simpleRJava_CellComm.R
+++ b/R/findpaths.simpleRJava_CellComm.R
@@ -127,7 +127,7 @@ setMethod("findpaths.simpleRJava",
                                   'FlowNetwork_all_paths_subnet.gml',
                                   format = 'gml');
             } else {
-              cat('No cells in the path', dir,'. The gaph was not created.\n')
+              cat('No cells in the path', dir,'. The graph was not created.\n')
             }
 
             # Change directory back to the original one.

From 84b20e48b328dac8cd7117dd993c2ff248bfcfa3 Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Thu, 5 May 2022 16:01:46 +0200
Subject: [PATCH 06/17] Update computeValue.R

---
 R/computeValue.R | 25 +++++++++++++++++--------
 1 file changed, 17 insertions(+), 8 deletions(-)

diff --git a/R/computeValue.R b/R/computeValue.R
index c15a45d..6d55ce5 100755
--- a/R/computeValue.R
+++ b/R/computeValue.R
@@ -17,20 +17,24 @@
 #' @docType methods
 #' @rdname computeValue-methods
 setGeneric("computeValue", function(object, assay.type='RNA',
-                                    genelist, column='population', fun='max')
+                                    genelist, column='population', fun='max', verbose = TRUE)
   standardGeneric("computeValue"))
 #' @rdname computeValue-methods
 #' @aliases computeValue
 setMethod("computeValue",
           signature = "CellRouter",
-          definition = function(object, assay.type, genelist, column, fun){
-            print('discovering subpopulation-specific gene signatures')
+          definition = function(object, assay.type, genelist, column, fun, verbose){
+            if(verbose == TRUE){
+              print('discovering subpopulation-specific gene signatures')
+            }
             expDat <- slot(object, 'assays')[[assay.type]]@ndata[genelist,]
             membs <- as.vector(slot(object, 'assays')[[assay.type]]@sampTab[[column]])
             membs_df <- as.vector(slot(object, 'assays')[[assay.type]]@sampTab[ , c('sample_id', column), drop=FALSE])
             diffs <- list()
             for(i in unique(membs)){
-              cat('cluster ', i, '\n')
+              if(verbose == TRUE){
+                cat('cluster ', i, '\n')
+              }
               if(sum(membs == i) == 0) next
               m_indexes <- membs_df[which(membs_df[[column]] != i), 'sample_id']
               n_indexes <- membs_df[which(membs_df[[column]] == i), 'sample_id']
@@ -85,15 +89,18 @@ setGeneric("computeValueSubclusters", function(object, assay.type='RNA',
                                                column='population',
                                                subcluster.column='Subpopulation',
                                                clusters,
-                                               fun='max')
+                                               fun='max',
+                                               verbose = TRUE)
   standardGeneric("computeValueSubclusters"))
 #' @rdname computeValueSubclusters-methods
 #' @aliases computeValueSubclusters
 setMethod("computeValueSubclusters",
           signature = "CellRouter",
           definition = function(object, assay.type, genelist, column,
-                                subcluster.column, clusters, fun){
-            print('discovering subpopulation-specific gene signatures')
+                                subcluster.column, clusters, fun, verbose){
+            if(verbose == TRUE){
+              print('discovering subpopulation-specific gene signatures')
+            }
             sampTab <- slot(object, 'assays')[[assay.type]]@sampTab[
               slot(object, 'assays')[[assay.type]]@sampTab[[column]] %in% clusters,]
             expDat <- slot(object, 'assays')[[assay.type]]@ndata[genelist, rownames(sampTab)]
@@ -101,7 +108,9 @@ setMethod("computeValueSubclusters",
             membs <- as.vector(sampTab[[subcluster.column]])
             diffs <- list()
             for(i in unique(membs)){
-              cat('cluster ', i, '\n')
+              if(verbose == TRUE){
+                cat('cluster ', i, '\n')
+              }
               if(sum(membs == i) == 0) next
               if(fun == 'max'){
                 m <- if(sum(membs != i) > 1) apply(expDat[, membs != i], 1, max) else expDat[, membs != i]

From 2e619bba15ab1b9dec956e5cc9746e7f4c7b3cf2 Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Thu, 5 May 2022 16:05:24 +0200
Subject: [PATCH 07/17] Update clusterPermutation_CellComm.R

---
 R/clusterPermutation_CellComm.R | 16 ++++++++++------
 1 file changed, 10 insertions(+), 6 deletions(-)

diff --git a/R/clusterPermutation_CellComm.R b/R/clusterPermutation_CellComm.R
index d034349..a15d0fd 100755
--- a/R/clusterPermutation_CellComm.R
+++ b/R/clusterPermutation_CellComm.R
@@ -17,16 +17,18 @@
 #'
 #' @export
 clusterPermutation <- function(cellrouter, assay.type='RNA', genelist,
-                               nPerm, interactions, cluster.label){
+                               nPerm, interactions, cluster.label, verbose=TRUE){
   pcellrouter <- cellrouter
   mean.pairs <- list()
   for(j in 1:nPerm){
-    cat(j, '______________________________\n')
+    if(verbose == TRUE){
+      cat(j, '______________________________\n')
+    }
     pclusters <- as.vector(slot(pcellrouter, 'assays')[[assay.type]]@sampTab[[cluster.label]])
     pclusters <- pclusters[sample(length(pclusters))]
     slot(pcellrouter, 'assays')[[assay.type]]@sampTab[[cluster.label]] <- pclusters
     mean.expr <- computeValue(pcellrouter, assay.type, genelist, cluster.label,
-                              fun='mean')
+                              fun='mean', verbose)
     # interactions <- population.pairing(mean.expr = mean.expr, ligands=ligands,
     #                                    receptors=receptors, threshold = 0.25, pairs.m)
     interactions2 <- interactions
@@ -76,7 +78,7 @@ clusterPermutation <- function(cellrouter, assay.type='RNA', genelist,
 clusterPermutationSubcluster <- function(cellrouter, assay.type='RNA', genelist,
                                          nPerm, interactions, cluster.label,
                                          subcluster.column='Subpopulation',
-                                         clusters){
+                                         clusters, verbose=TRUE){
   pcellrouter <- cellrouter
   sampTab <- slot(pcellrouter, 'assays')[[assay.type]]@sampTab[
     slot(pcellrouter, 'assays')[[assay.type]]@sampTab[[cluster.label]] %in% clusters, ]
@@ -85,7 +87,9 @@ clusterPermutationSubcluster <- function(cellrouter, assay.type='RNA', genelist,
   slot(pcellrouter, 'assays')[[assay.type]]@ndata <- expDat
   mean.pairs <- list()
   for(j in 1:nPerm){
-    cat(j, '______________________________\n')
+    if(verbose == TRUE){
+      cat(j, '______________________________\n')
+    }
     pclusters <- as.vector(slot(pcellrouter, 'assays')[[assay.type]]@sampTab[[subcluster.column]])
     pclusters <- pclusters[sample(length(pclusters))]
     slot(pcellrouter, 'assays')[[assay.type]]@sampTab[[subcluster.column]] <- pclusters
@@ -94,7 +98,7 @@ clusterPermutationSubcluster <- function(cellrouter, assay.type='RNA', genelist,
                                          genelist = genelist,
                                          column = cluster.label,
                                          subcluster.column = subcluster.column,
-                                         clusters = clusters, fun='mean')
+                                         clusters = clusters, fun='mean', verbose)
     # interactions <- population.pairing(mean.expr = mean.expr, ligands=ligands,
     #                                    receptors=receptors, threshold = 0.25, pairs.m)
     interactions2 <- interactions

From 2c12a71084ceccab65d6ac944e9c1257a5fe6dfe Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Thu, 5 May 2022 16:22:00 +0200
Subject: [PATCH 08/17] Update computeValue.R

---
 R/computeValue.R | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/R/computeValue.R b/R/computeValue.R
index 6d55ce5..2ffd2e8 100755
--- a/R/computeValue.R
+++ b/R/computeValue.R
@@ -27,6 +27,10 @@ setMethod("computeValue",
             if(verbose == TRUE){
               print('discovering subpopulation-specific gene signatures')
             }
+            genelist <- unique(intersect(genelist, rownames(slot(object, 'assays')[[assay.type]]@ndata)))
+            if (length(genelist) == 0) {
+              stop("Error no matching between the genelist and the assay")
+            }
             expDat <- slot(object, 'assays')[[assay.type]]@ndata[genelist,]
             membs <- as.vector(slot(object, 'assays')[[assay.type]]@sampTab[[column]])
             membs_df <- as.vector(slot(object, 'assays')[[assay.type]]@sampTab[ , c('sample_id', column), drop=FALSE])

From 4593093503964c0d611974f59b7945a3d6615161 Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Thu, 5 May 2022 16:24:47 +0200
Subject: [PATCH 09/17] Create Omnipath_LR_network.R

---
 R/Omnipath_LR_network.R | 48 +++++++++++++++++++++++++++++++++++++++++
 1 file changed, 48 insertions(+)
 create mode 100644 R/Omnipath_LR_network.R

diff --git a/R/Omnipath_LR_network.R b/R/Omnipath_LR_network.R
new file mode 100644
index 0000000..f9368f5
--- /dev/null
+++ b/R/Omnipath_LR_network.R
@@ -0,0 +1,48 @@
+#' Create protein-protein interactions.
+#'
+#' Create a protein-protein interaction network for the reconstruction of cell
+#' signaling pathways.
+#'
+#' @param filename character; protein interaction data.
+#' @param expr dgCMatrix; gene expression in each cell, found in
+#' CellRouter@@ndata.
+#'
+#' @return list; the network (igraph object), the ctable (data frame) with the
+#' edge list, the table (data frame) with the information of the ids of gene A
+#' and B and the scores, the genes in total (character vector), genesPPI
+#' (character vector) with the genes in the interactions, and the remove
+#' (character vector) with the genes not used in the interactions.
+#'
+#' @export
+createPPI <- function(expr, species){
+  a <- expr
+  if (species = "Hs") {
+    organism <- 9606
+  }
+  else if (species = "Mm") {
+    organism <- 10090
+  }
+  else if (species = "Rn") {
+    organism <- 10116
+  }
+  data <- as.data.frame(import_omnipath_interactions(datasets = 'omnipath', entity_types = 'protein', organism = organism))
+  cat(dim(ppi))
+  cat('\nProtein interaction data loaded!')
+  # The columns names are usually fixed.
+  ppi <- data[, c('source_genesymbol','target_genesymbol', 'curation_effort')] #geneA and geneB, score
+  idmap <- data.frame(idA=ppi$source_genesymbol, idB=ppi$target_genesymbol, score=as.numeric(ppi$curation_effort))
+  allgenes <- unique(c(as.vector(idmap$idA), as.vector(idmap$idB)))
+  inetwork <- igraph::graph.data.frame(idmap, directed=FALSE);
+  inetwork <- igraph::simplify(inetwork, remove.multiple = TRUE,
+                               remove.loops = TRUE)
+  genesPPI <- intersect(rownames(expr), allgenes)
+  remove <- setdiff(igraph::V(inetwork)$name, rownames(expr))
+  inetwork <- igraph::delete.vertices(inetwork, remove)
+  ctable <- as.data.frame(igraph::get.edgelist(inetwork))
+  colnames(ctable) <- c('from', 'to')
+  names <- paste(as.vector(ctable$from), as.vector(ctable$to), sep="_")
+  rownames(ctable) <- names
+  network <- list(network=inetwork, ctable=ctable, table=idmap, genes=allgenes,
+                  genesPPI=genesPPI, removed=remove)
+  return(network)
+}

From 3ebced24a90c17ecf7fe2bb049ad9f14fb47e666 Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Thu, 5 May 2022 16:29:04 +0200
Subject: [PATCH 10/17] Update Omnipath_LR_network.R

---
 R/Omnipath_LR_network.R | 35 ++++-------------------------------
 1 file changed, 4 insertions(+), 31 deletions(-)

diff --git a/R/Omnipath_LR_network.R b/R/Omnipath_LR_network.R
index f9368f5..f7160ae 100644
--- a/R/Omnipath_LR_network.R
+++ b/R/Omnipath_LR_network.R
@@ -14,35 +14,8 @@
 #' (character vector) with the genes not used in the interactions.
 #'
 #' @export
-createPPI <- function(expr, species){
-  a <- expr
-  if (species = "Hs") {
-    organism <- 9606
-  }
-  else if (species = "Mm") {
-    organism <- 10090
-  }
-  else if (species = "Rn") {
-    organism <- 10116
-  }
-  data <- as.data.frame(import_omnipath_interactions(datasets = 'omnipath', entity_types = 'protein', organism = organism))
-  cat(dim(ppi))
-  cat('\nProtein interaction data loaded!')
-  # The columns names are usually fixed.
-  ppi <- data[, c('source_genesymbol','target_genesymbol', 'curation_effort')] #geneA and geneB, score
-  idmap <- data.frame(idA=ppi$source_genesymbol, idB=ppi$target_genesymbol, score=as.numeric(ppi$curation_effort))
-  allgenes <- unique(c(as.vector(idmap$idA), as.vector(idmap$idB)))
-  inetwork <- igraph::graph.data.frame(idmap, directed=FALSE);
-  inetwork <- igraph::simplify(inetwork, remove.multiple = TRUE,
-                               remove.loops = TRUE)
-  genesPPI <- intersect(rownames(expr), allgenes)
-  remove <- setdiff(igraph::V(inetwork)$name, rownames(expr))
-  inetwork <- igraph::delete.vertices(inetwork, remove)
-  ctable <- as.data.frame(igraph::get.edgelist(inetwork))
-  colnames(ctable) <- c('from', 'to')
-  names <- paste(as.vector(ctable$from), as.vector(ctable$to), sep="_")
-  rownames(ctable) <- names
-  network <- list(network=inetwork, ctable=ctable, table=idmap, genes=allgenes,
-                  genesPPI=genesPPI, removed=remove)
-  return(network)
+Omnipath_LR_network <- function(species){
+  pairs <- nichenet_lr_network(only_omnipath = TRUE)
+  pairs$Pair.Name <- paste(pairs$from, pairs$to, sep = "_")
+  return(pairs)
 }

From d748c968c8efe1610c63bb8f25653d8ba0232812 Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Thu, 5 May 2022 16:38:23 +0200
Subject: [PATCH 11/17] Create Path_finding.R

---
 R/Path_finding.R | 46 ++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 46 insertions(+)
 create mode 100644 R/Path_finding.R

diff --git a/R/Path_finding.R b/R/Path_finding.R
new file mode 100644
index 0000000..c607e48
--- /dev/null
+++ b/R/Path_finding.R
@@ -0,0 +1,46 @@
+#' Compute cell-cell interaction network.
+#'
+#' Analyze the mean expression data generated by the computeValue method of
+#' CellRouter to determine co-expression patterns of ligands and receptors.
+#'
+#' @param mean.expr list; the statistics of the expressed genes as calculated by
+#' the computeValue method of CellRouter.
+#' @param ligands vector; list of genes annotated as ligands.
+#' @param receptors vector; list of genes annotated as receptors.
+#' @param threshold numeric; threshold to select the genes in the population
+#' according to their mean expression.
+#' @param pairs the pairs;
+#'
+#' @return data frame; interactions with celltype1, celltype2, pair, ligand,
+#' and receptor.
+#'
+#' @export
+population.pairing <- function(mean.expr, ligands, receptors, threshold, pairs){
+  interactions <- list()
+  for(ct1 in names(mean.expr)){
+    for(ct2 in names(mean.expr)){
+      ct1.expressed <- mean.expr[[ct1]][c(ligands, receptors),]
+      ct1.expressed <- ct1.expressed[which(ct1.expressed$p > threshold),]
+
+      ct2.expressed <- mean.expr[[ct2]][c(ligands, receptors),]
+      ct2.expressed <- ct2.expressed[which(ct2.expressed$p > threshold),]
+
+      combs <- expand.grid(rownames(ct1.expressed), rownames(ct2.expressed))
+      combs <- paste(combs$Var1, combs$Var2, sep='_')
+      combs <- intersect(combs, pairs$Pair.Name)
+      if(length(combs) > 0){
+        ligs <- sapply(strsplit(combs, split='_', fixed=TRUE), function(x) (x[1]))
+        recs <- sapply(strsplit(combs, split='_', fixed=TRUE), function(x) (x[2]))
+        df <- data.frame(celltype1=rep(ct1, times=length(combs)),
+                         celltype2=rep(ct2, times=length(combs)),
+                         pair=combs, ligand=ligs, receptor=recs,
+                         stringsAsFactors = FALSE)
+        interactions[[paste(ct1,ct2,sep='_')]] <- df
+      }
+
+    }
+  }
+  interactions <- dplyr::bind_rows(interactions)#rbind.fill(interactions)
+
+  return(interactions)
+}

From 30cd82f58178a376b9e60b04e1d3603d46e39a74 Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Thu, 5 May 2022 16:50:48 +0200
Subject: [PATCH 12/17] Update Path_finding.R

---
 R/Path_finding.R | 62 ++++++++++++++++++++++++++++++------------------
 1 file changed, 39 insertions(+), 23 deletions(-)

diff --git a/R/Path_finding.R b/R/Path_finding.R
index c607e48..70fda92 100644
--- a/R/Path_finding.R
+++ b/R/Path_finding.R
@@ -15,32 +15,48 @@
 #' and receptor.
 #'
 #' @export
-population.pairing <- function(mean.expr, ligands, receptors, threshold, pairs){
-  interactions <- list()
-  for(ct1 in names(mean.expr)){
-    for(ct2 in names(mean.expr)){
-      ct1.expressed <- mean.expr[[ct1]][c(ligands, receptors),]
-      ct1.expressed <- ct1.expressed[which(ct1.expressed$p > threshold),]
+pathfinding <- function(cellrouter, assay.type='ST', grn, gene.pairs_01, gene.pairs_02, markers, maindir=NULL, verbose=TRUE){
+  tfs <- intersect(grn.data$tfs, rownames(slot(object, 'assays')[[assay.type]]@ndata))
+  x <- rbind(gene.pairs_01$markers, gene.pairs_02$markers)
 
-      ct2.expressed <- mean.expr[[ct2]][c(ligands, receptors),]
-      ct2.expressed <- ct2.expressed[which(ct2.expressed$p > threshold),]
+  sts2 <- list()
+  for(i in unique(x$celltypes)){
+    tmp <- x[which(x$celltypes == i),]
+    rs <- unique(tmp$receptor)
+    sts2[["receptor"]][[i]]$sources <- rs  # receptors
+    sts2[["receptor"]][[i]]$targets <- tfs # TFs (all)
+  }
+  if (maindir == NULL) {
+    wd_package <- getwd()
+    setwd(wd_package)
+    maindir <- paste0(wd_package, '')
+  }
+  
+  interactionList <- expand.grid(x$celltypes)
 
-      combs <- expand.grid(rownames(ct1.expressed), rownames(ct2.expressed))
-      combs <- paste(combs$Var1, combs$Var2, sep='_')
-      combs <- intersect(combs, pairs$Pair.Name)
-      if(length(combs) > 0){
-        ligs <- sapply(strsplit(combs, split='_', fixed=TRUE), function(x) (x[1]))
-        recs <- sapply(strsplit(combs, split='_', fixed=TRUE), function(x) (x[2]))
-        df <- data.frame(celltype1=rep(ct1, times=length(combs)),
-                         celltype2=rep(ct2, times=length(combs)),
-                         pair=combs, ligand=ligs, receptor=recs,
-                         stringsAsFactors = FALSE)
-        interactions[[paste(ct1,ct2,sep='_')]] <- df
-      }
+  cellcomm <- CreateCellComm()
+  for(interaction in interactionList){
+    interaction <- gsub(" ", ".", interaction)
+    print(interaction)
+    celltype <- strsplit(interaction, split = "[_]")[[1]][2]
+  
+    cat("Using ", celltype, " coexpression network\n")
+    filename <- paste(celltype, ".txt", sep='')
+    dirname <- gsub(("[.]"), ".", interaction)
+    cellcomm <- findpaths.simpleRJava(cellcomm, sources.targets = sts2$receptor[[interaction]], file = filename, dir = dirname, maindir = maindir)
+  }
 
-    }
+  files <- list()
+  for(i in interactionList){
+    f <- paste(strsplit(i, split = "_")[[1]][2], ".txt", sep = "")
+    files[[i]] <- f
   }
-  interactions <- dplyr::bind_rows(interactions)#rbind.fill(interactions)
 
-  return(interactions)
+  summary <- summarize.flow(files, prefix = "")
+  colnames(grn_table) <- c("target", "reg", "zscore", "corr")
+  sampTab <- slot(object, 'assays')[[assay.type]]@sampTab
+  apathways <- activeSignaling(data = slot(object, 'assays')[[assay.type]]@ndata, sampTab = slot(object, 'assays')[[assay.type]]@sampTab,
+                             grn = grn$GRN_table, markers = markers, summary = summary, fc = 0.2)
+  npaths <- rankpaths(summary, apathways$pathways)
+  return(npaths)
 }

From 6fbc81274b7898f2cb092591491c31a4bec2f4f6 Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Fri, 6 May 2022 10:48:43 +0200
Subject: [PATCH 13/17] Update Omnipath_LR_network.R

---
 R/Omnipath_LR_network.R | 19 ++++---------------
 1 file changed, 4 insertions(+), 15 deletions(-)

diff --git a/R/Omnipath_LR_network.R b/R/Omnipath_LR_network.R
index f7160ae..fe68129 100644
--- a/R/Omnipath_LR_network.R
+++ b/R/Omnipath_LR_network.R
@@ -1,21 +1,10 @@
-#' Create protein-protein interactions.
+#' Builds ligand-receptor network prior knowledge for fusca using Omnipath.
 #'
-#' Create a protein-protein interaction network for the reconstruction of cell
-#' signaling pathways.
-#'
-#' @param filename character; protein interaction data.
-#' @param expr dgCMatrix; gene expression in each cell, found in
-#' CellRouter@@ndata.
-#'
-#' @return list; the network (igraph object), the ctable (data frame) with the
-#' edge list, the table (data frame) with the information of the ids of gene A
-#' and B and the scores, the genes in total (character vector), genesPPI
-#' (character vector) with the genes in the interactions, and the remove
-#' (character vector) with the genes not used in the interactions.
+#' @return data frame containing ligand and receptor.
 #'
 #' @export
-Omnipath_LR_network <- function(species){
-  pairs <- nichenet_lr_network(only_omnipath = TRUE)
+Omnipath_LR_network <- function(){
+  pairs <- nichenet_lr_network(ramilowski = NULL)
   pairs$Pair.Name <- paste(pairs$from, pairs$to, sep = "_")
   return(pairs)
 }

From f265e1c948ce48afc5dc4a344f1232347edfdee4 Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Fri, 6 May 2022 10:56:38 +0200
Subject: [PATCH 14/17] Update clusterPermutation_CellComm.R

---
 R/clusterPermutation_CellComm.R | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/R/clusterPermutation_CellComm.R b/R/clusterPermutation_CellComm.R
index a15d0fd..f17d19b 100755
--- a/R/clusterPermutation_CellComm.R
+++ b/R/clusterPermutation_CellComm.R
@@ -11,6 +11,7 @@
 #' population.pairing function or the calculateObservedMean function.
 #' @param cluster.label character; column in the metadata table
 #' (CellRouter@@sampTab) corresponding to the population.
+#' @param verbose boolean; verbosity of the function.
 #'
 #' @return list; the interaction data frame for each permutation, including the
 #' columns of mean expression of ligands, receptors and pairs.
@@ -70,6 +71,7 @@ clusterPermutation <- function(cellrouter, assay.type='RNA', genelist,
 #' @param subcluster.column character; the name of the column where the
 #' subclustering information will be stored.
 #' @param clusters character; selected clusters.
+#' @param verbose boolean; verbosity of the function.
 #'
 #' @return list; the interaction data frame for each permutation, including the
 #' columns of mean expression of ligands, receptors and pairs.

From 07159a58ca00988af6fbf0f11a15b1062fa1d517 Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Fri, 6 May 2022 10:57:59 +0200
Subject: [PATCH 15/17] Update computeValue.R

---
 R/computeValue.R | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/R/computeValue.R b/R/computeValue.R
index 2ffd2e8..182166c 100755
--- a/R/computeValue.R
+++ b/R/computeValue.R
@@ -9,6 +9,7 @@
 #' differential expression. For example, if 'population' is specified,
 #' population-specific gene signatures will be identified.
 #' @param fun character; statistical function to summary the gene expression.
+#' @param verbose boolean; verbosity of the function.
 #'
 #' @return list; the statistics of the expressed genes in the population (p
 #' column), not in the population (np), and the percentage (percent).
@@ -81,6 +82,7 @@ detectGenes <- function(expr, min_expr = 0.1){
 #' subclustering information will be stored.
 #' @param clusters character; selected clusters.
 #' @param fun character; statistical function to summary the gene expression.
+#' @param verbose boolean; verbosity of the function.
 #'
 #' @return list; the statistics of the expressed genes in the population (p
 #' column), not in the population (np), and the percentage (percent).

From eb0f23f5aef64e9fb43ef1706872d648f461fc09 Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Fri, 6 May 2022 12:18:07 +0200
Subject: [PATCH 16/17] Update createPPI_OmniPath.R

---
 R/createPPI_OmniPath.R | 13 ++++++++-----
 1 file changed, 8 insertions(+), 5 deletions(-)

diff --git a/R/createPPI_OmniPath.R b/R/createPPI_OmniPath.R
index f9368f5..fdb1d31 100644
--- a/R/createPPI_OmniPath.R
+++ b/R/createPPI_OmniPath.R
@@ -1,11 +1,12 @@
 #' Create protein-protein interactions.
 #'
 #' Create a protein-protein interaction network for the reconstruction of cell
-#' signaling pathways.
+#' signaling pathways from OmniPath.
 #'
-#' @param filename character; protein interaction data.
 #' @param expr dgCMatrix; gene expression in each cell, found in
 #' CellRouter@@ndata.
+#' @param species character; defining the species: Hs for Homo Sapiens, Mm for Mus Musculus or Rn for Rattus norvegicus.
+#' @param verbose boolean; verbosity of the function.
 #'
 #' @return list; the network (igraph object), the ctable (data frame) with the
 #' edge list, the table (data frame) with the information of the ids of gene A
@@ -14,7 +15,7 @@
 #' (character vector) with the genes not used in the interactions.
 #'
 #' @export
-createPPI <- function(expr, species){
+createPPIOmniPath <- function(expr, species = "Hs", verbose = TRUE){
   a <- expr
   if (species = "Hs") {
     organism <- 9606
@@ -26,8 +27,10 @@ createPPI <- function(expr, species){
     organism <- 10116
   }
   data <- as.data.frame(import_omnipath_interactions(datasets = 'omnipath', entity_types = 'protein', organism = organism))
-  cat(dim(ppi))
-  cat('\nProtein interaction data loaded!')
+  if(verbose == TRUE){
+    cat(dim(ppi))
+    cat('\nProtein interaction data loaded!')
+  }
   # The columns names are usually fixed.
   ppi <- data[, c('source_genesymbol','target_genesymbol', 'curation_effort')] #geneA and geneB, score
   idmap <- data.frame(idA=ppi$source_genesymbol, idB=ppi$target_genesymbol, score=as.numeric(ppi$curation_effort))

From 156242fe1afff5e849a4d8de6b86baaa38222a9d Mon Sep 17 00:00:00 2001
From: Goultard59 <goultard59@gmail.com>
Date: Fri, 6 May 2022 12:27:44 +0200
Subject: [PATCH 17/17] Delete Path_finding.R

---
 R/Path_finding.R | 62 ------------------------------------------------
 1 file changed, 62 deletions(-)
 delete mode 100644 R/Path_finding.R

diff --git a/R/Path_finding.R b/R/Path_finding.R
deleted file mode 100644
index 70fda92..0000000
--- a/R/Path_finding.R
+++ /dev/null
@@ -1,62 +0,0 @@
-#' Compute cell-cell interaction network.
-#'
-#' Analyze the mean expression data generated by the computeValue method of
-#' CellRouter to determine co-expression patterns of ligands and receptors.
-#'
-#' @param mean.expr list; the statistics of the expressed genes as calculated by
-#' the computeValue method of CellRouter.
-#' @param ligands vector; list of genes annotated as ligands.
-#' @param receptors vector; list of genes annotated as receptors.
-#' @param threshold numeric; threshold to select the genes in the population
-#' according to their mean expression.
-#' @param pairs the pairs;
-#'
-#' @return data frame; interactions with celltype1, celltype2, pair, ligand,
-#' and receptor.
-#'
-#' @export
-pathfinding <- function(cellrouter, assay.type='ST', grn, gene.pairs_01, gene.pairs_02, markers, maindir=NULL, verbose=TRUE){
-  tfs <- intersect(grn.data$tfs, rownames(slot(object, 'assays')[[assay.type]]@ndata))
-  x <- rbind(gene.pairs_01$markers, gene.pairs_02$markers)
-
-  sts2 <- list()
-  for(i in unique(x$celltypes)){
-    tmp <- x[which(x$celltypes == i),]
-    rs <- unique(tmp$receptor)
-    sts2[["receptor"]][[i]]$sources <- rs  # receptors
-    sts2[["receptor"]][[i]]$targets <- tfs # TFs (all)
-  }
-  if (maindir == NULL) {
-    wd_package <- getwd()
-    setwd(wd_package)
-    maindir <- paste0(wd_package, '')
-  }
-  
-  interactionList <- expand.grid(x$celltypes)
-
-  cellcomm <- CreateCellComm()
-  for(interaction in interactionList){
-    interaction <- gsub(" ", ".", interaction)
-    print(interaction)
-    celltype <- strsplit(interaction, split = "[_]")[[1]][2]
-  
-    cat("Using ", celltype, " coexpression network\n")
-    filename <- paste(celltype, ".txt", sep='')
-    dirname <- gsub(("[.]"), ".", interaction)
-    cellcomm <- findpaths.simpleRJava(cellcomm, sources.targets = sts2$receptor[[interaction]], file = filename, dir = dirname, maindir = maindir)
-  }
-
-  files <- list()
-  for(i in interactionList){
-    f <- paste(strsplit(i, split = "_")[[1]][2], ".txt", sep = "")
-    files[[i]] <- f
-  }
-
-  summary <- summarize.flow(files, prefix = "")
-  colnames(grn_table) <- c("target", "reg", "zscore", "corr")
-  sampTab <- slot(object, 'assays')[[assay.type]]@sampTab
-  apathways <- activeSignaling(data = slot(object, 'assays')[[assay.type]]@ndata, sampTab = slot(object, 'assays')[[assay.type]]@sampTab,
-                             grn = grn$GRN_table, markers = markers, summary = summary, fc = 0.2)
-  npaths <- rankpaths(summary, apathways$pathways)
-  return(npaths)
-}