netZoo
diff --git a/‎DESCRIPTION‎
Lines changed: 41 additions & 34 deletions b/‎DESCRIPTION‎
Lines changed: 41 additions & 34 deletions
diff --git a/‎NAMESPACE‎
Lines changed: 8 additions & 0 deletions b/‎NAMESPACE‎
Lines changed: 8 additions & 0 deletions
diff --git a/‎R/MONSTER.R‎
Lines changed: 5 additions & 5 deletions b/‎R/MONSTER.R‎
Lines changed: 5 additions & 5 deletions
diff --git a/‎R/PUMA.R‎
Lines changed: 5 additions & 4 deletions b/‎R/PUMA.R‎
Lines changed: 5 additions & 4 deletions
@@ -1,8 +1,8 @@
 Package: netZooR
 Type: Package
 Title: Unified methods for the inference and analysis of gene regulatory networks
-Version: 1.3.15
-Date: 2023-03-16
+Version: 1.4.0
+Date: 2023-06-03
 Authors@R: c(person("Marouen", "Ben Guebila",
 			email = "benguebila@hsph.harvard.edu", role = c("aut","cre"), comment = c(ORCID = "0000-0001-5934-966X")),
 	     person("Tian", "Wang", 
@@ -27,6 +27,8 @@ Depends: R (>= 4.2.0),
          pandaR,
          yarn,
          matrixcalc
+Remotes: 
+	 stan-dev/cmdstanr 
 biocViews:
 	 NetworkInference,
 	 Network,
@@ -35,45 +37,50 @@ biocViews:
          Transcription, 
          Microarray,   
          GraphAndNetwork
-Imports: RCy3,
-	 viridisLite, 
-   STRINGdb,
-	 Biobase,
-	 GOstats,
-	 AnnotationDbi,
-   matrixStats,
-   GO.db,
-	 org.Hs.eg.db,
-	 Matrix,
-	 gplots,
-	 nnet,
-	 data.table,
-	 vegan,
-	 stats,
-	 utils,
-   reshape,
-   reshape2,
-   penalized,
-   parallel,
-   doParallel,
-   foreach,
-   ggplot2,
-   ggdendro,
-   grid,
-   MASS,
-   assertthat,
-   tidyr,
-   methods,
-   dplyr,
-   graphics
+Imports: 
+    RCy3,
+    viridisLite,
+    STRINGdb,
+    Biobase,
+    GOstats,
+    AnnotationDbi,
+    matrixStats,
+    GO.db,
+    org.Hs.eg.db,
+    Matrix,
+    gplots,
+    nnet,
+    data.table,
+    vegan,
+    stats,
+    utils,
+    reshape,
+    reshape2,
+    penalized,
+    parallel,
+    doParallel,
+    foreach,
+    ggplot2,
+    ggdendro,
+    grid,
+    MASS,
+    assertthat,
+    tidyr,
+    methods,
+    dplyr,
+    graphics,
+	cmdstanr,
+    GeneNet,
+    loo
 License: GPL-3
 Encoding: UTF-8
 LazyData: false
 Suggests: 
     testthat (>= 2.1.0),
     knitr,
     rmarkdown,
-    pkgdown
+    pkgdown,
+    dorothea
 VignetteEngine: knitr
 VignetteBuilder: knitr
 RoxygenNote: 7.2.3
 
@@ -1,5 +1,8 @@
 # Generated by roxygen2: do not edit by hand
 
+export(TIGER)
+export(adj2el)
+export(adj2regulon)
 export(alpaca)
 export(alpacaCrane)
 export(alpacaExtractTopGenes)
@@ -15,6 +18,8 @@ export(craneUnipartite)
 export(createCondorObject)
 export(createPandaStyle)
 export(dragon)
+export(el2adj)
+export(el2regulon)
 export(elistToAdjMat)
 export(lioness)
 export(lionessPy)
@@ -36,6 +41,8 @@ export(pandaDiffEdges)
 export(pandaPy)
 export(pandaToAlpaca)
 export(pandaToCondorObject)
+export(prior.pp)
+export(puma)
 export(runEgret)
 export(sambar)
 export(sourcePPI)
@@ -87,6 +94,7 @@ importFrom(matrixStats,rowSds)
 importFrom(methods,is)
 importFrom(methods,new)
 importFrom(pandaR,panda)
+importFrom(parallel,mclapply)
 importFrom(penalized,optL1)
 importFrom(penalized,penalized)
 importFrom(penalized,predict)
 
@@ -27,9 +27,9 @@ monsterGetTm <- function(x){
 #' data(yeast)
 #' yeast$exp.cc[is.na(yeast$exp.cc)] <- mean(as.matrix(yeast$exp.cc),na.rm=TRUE)
 #' design <- c(rep(1,25),rep(0,10),rep(NA,15))
-#' monsterRes <- monster(yeast$exp.cc, design,
-#' yeast$motif, nullPerms=10, numMaxCores=1)
-#' monsterPlotMonsterAnalysis(monsterRes)
+#' #monsterRes <- monster(yeast$exp.cc, design,
+#' #yeast$motif, nullPerms=10, numMaxCores=1)
+#' #monsterPlotMonsterAnalysis(monsterRes)
 monsterPlotMonsterAnalysis <- function(x, ...){
   monsterdTFIPlot(x,...)
 }
@@ -46,7 +46,7 @@ monsterPlotMonsterAnalysis <- function(x, ...){
 #' data(yeast)
 #' yeast$exp.cc[is.na(yeast$exp.cc)] <- mean(as.matrix(yeast$exp.cc),na.rm=TRUE)
 #' design <- c(rep(1,25),rep(0,10),rep(NA,15))
-#' monster(yeast$exp.cc,design,yeast$motif, nullPerms=10, numMaxCores=1)
+#' #monster(yeast$exp.cc,design,yeast$motif, nullPerms=10, numMaxCores=1)
 monsterPrintMonsterAnalysis <- function(x, ...){
   cat("MONSTER object\n")
   cat(paste(x@numGenes, "genes\n"))
@@ -103,7 +103,7 @@ monsterPrintMonsterAnalysis <- function(x, ...){
 #' data(yeast)
 #' design <- c(rep(0,20),rep(NA,10),rep(1,20))
 #' yeast$exp.cc[is.na(yeast$exp.cc)] <- mean(as.matrix(yeast$exp.cc),na.rm=TRUE)
-#' monsterRes <- monster(yeast$exp.cc[1:500,], design, yeast$motif, nullPerms=10, numMaxCores=1)
+#' #monsterRes <- monster(yeast$exp.cc[1:500,], design, yeast$motif, nullPerms=10, numMaxCores=1)
 #' # Example with provided networks
 #' \donttest{
 #' pandaResult <- panda(pandaToyData$motif, pandaToyData$expression, pandaToyData$ppi)
 
@@ -45,8 +45,9 @@
 #' "coopNet" is the cooperative network which is not updated for miRNAs
 #' @examples
 #' data(pandaToyData)
+#' mirs = c("AHR","AR","ARID3A","ARNT","BRCA1","CEBPA","CREB1","DDIT3")
 #' pumaRes <- puma(pandaToyData$motif,
-#'            pandaToyData$expression,NULL,hamming=.1,progress=TRUE)
+#'            pandaToyData$expression,NULL,mir_file=mirs,hamming=.1,progress=TRUE)
 #' @references
 #' Kuijjer, Marieke L., et al. "PUMA: PANDA using microRNA associations." Bioinformatics 36.18 (2020): 4765-4773.
 puma <- function(motif,expr=NULL,ppi=NULL,alpha=0.1,mir_file,hamming=0.001,
@@ -238,11 +239,11 @@ puma <- function(motif,expr=NULL,ppi=NULL,alpha=0.1,mir_file,hamming=0.001,
     rownames(tfCoopNetwork) <- tf.names
   }
 
-  if(mir_file != NULL){
+  if(!is.null(mir_file)){
     mirIndex = match(mir_file,tf.names)
     tfCoopNetwork[mirIndex,] = 0
     tfCoopNetwork[,mirIndex] = 0
-    seqs = seq(1, num.tfs*num.tfs, num.tfs+1)
+    seqs = seq(1, num.TFs*num.TFs, num.TFs+1)
     tfCoopNetwork[seqs] <- 1
     # tfCoopNetwork has now a diagonal of 1 and all entries are zeros 
     # for miRNA-miRNA interactions and TF-miRNA interactions
@@ -288,7 +289,7 @@ puma <- function(motif,expr=NULL,ppi=NULL,alpha=0.1,mir_file,hamming=0.001,
     geneCoreg=minusAlpha*geneCoreg + alpha*CoReg2
 
     #PUMA step to skip update of PPI matrix for miRNA interactions
-    seqs = seq(1, num.tfs*num.tfs, num.tfs+1)
+    seqs = seq(1, num.TFs*num.TFs, num.TFs+1)
     savediag = tfCoopNetwork[seqs] # save diagonal
     tfCoopNetwork[mirIndex,] <- TFCoopInit[mirIndex,]
     tfCoopNetwork[,mirIndex] <- TFCoopInit[,mirIndex]