v-0.99.3

DESCRIPTION

@@ -1,14 +1,14 @@
 Package: scTensor
 Type: Package
 Title: Detection and visualization of cell-cell interaction within single-cell RNA-Seq data
-Version: 0.99.2
+Version: 0.99.3
 Date: 2018-09-25
 Author: Koki Tsuyuzaki
 Maintainer: Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>
 Depends: R (>= 3.5.0)
-Imports: methods, igraph, S4Vectors, plotly, AnnotationDbi, reactome.db, SummarizedExperiment, SingleCellExperiment, nnTensor, rTensor, LRBaseDbi, abind, plotrix, heatmaply, tagcloud, RColorBrewer, rmarkdown, BiocStyle, knitr, biomaRt, LRBase.Hsa.eg.db, MeSH.Hsa.eg.db, MeSHDbi, meshr, GOstats, ReactomePA, grDevices, graphics, stats, utils, outliers, snow, Category
+Imports: methods, igraph, S4Vectors, plotly, reactome.db, AnnotationDbi, SummarizedExperiment, SingleCellExperiment, nnTensor, rTensor, LRBaseDbi, abind, plotrix, heatmaply, tagcloud, rmarkdown, BiocStyle, knitr, biomaRt, LRBase.Hsa.eg.db, MeSH.Hsa.eg.db, MeSHDbi, GOstats, ReactomePA, grDevices, graphics, stats, utils, outliers, snow, Category
 Suggests: testthat, RSQLite, LRBase.Mmu.eg.db, MeSH.Mmu.eg.db
-Description: The algorithm is based on non-negative tucker decomposition (NTD) of nnTensor.
+Description: The algorithm is based on the non-negative tucker decomposition (NTD) of nnTensor.
 License: Artistic-2.0
 biocViews: DimensionReduction, SingleCell
 VignetteBuilder: knitr

NAMESPACE

@@ -1,15 +1,14 @@
 import(methods)
-import(igraph)
 import(SingleCellExperiment)
-import(nnTensor)
 import(BiocStyle)
 import(knitr)
 import(MeSH.Hsa.eg.db)
 import(LRBase.Hsa.eg.db)
 import(GOstats)
 
-importFrom(reactome.db, reactomeEXTID2PATHID)
 importFrom(AnnotationDbi, toTable)
+importFrom(igraph, graph.empty, add.vertices, add.edges, "E<-", "V<-", V, E, layout_with_dh, plot.igraph, get.edgelist)
+importFrom(reactome.db, reactomeEXTID2PATHID)
 importFrom(LRBaseDbi, select)
 importFrom(biomaRt, useMart, getBM)
 importFrom(MeSHDbi, select)
@@ -21,18 +20,16 @@ importFrom(abind, abind)
 importFrom(plotrix, gradient.rect)
 importFrom(heatmaply, heatmaply)
 importFrom(tagcloud, smoothPalette, tagcloud)
-importFrom(RColorBrewer, brewer.pal)
 importFrom(rmarkdown, render)
 
 importFrom(grDevices, colorRampPalette, dev.off, png, rgb)
 importFrom(graphics, par, plot, text, legend)
 importFrom(stats, cor, dist, na.omit, quantile, p.adjust, hclust, cutree)
 importFrom(utils, browseURL, txtProgressBar, setTxtProgressBar)
 importFrom(outliers, grubbs.test, chisq.out.test)
-importFrom(meshr, meshHyperGTest)
+importFrom(nnTensor, NMF, NTD, recTensor)
 importFrom(ReactomePA, enrichPathway)
 importFrom(snow, clusterExport, parSapply, clusterEvalQ)
 importFrom(Category, hyperGTest)
 
-
-exportMethods(cellCellSetting, cellCellRanks, cellCellDecomp, cellCellReport)
+exportMethods(cellCellSetting, cellCellRanks, cellCellDecomp, cellCellReport)

R/AllGenerics.R

@@ -206,6 +206,8 @@ setMethod("cellCellDecomp", signature(sce="SingleCellExperiment"),
     # Output
 }
 
+
+
 #
 # cellCellReport
 #
@@ -337,11 +339,10 @@ setMethod("cellCellReport", signature(sce="SingleCellExperiment"),
                 library("outliers")
                 library("S4Vectors")
                 library("tagcloud")
-                library("RColorBrewer")
                 library("plotrix")
                 library("plotly")
                 library("rmarkdown")
-                library("meshr")
+                # library("meshr")
                 library("GOstats")
                 library("ReactomePA")
             }))
@@ -392,8 +393,8 @@ setMethod("cellCellReport", signature(sce="SingleCellExperiment"),
     vecR <- metadata(sce)$sctensor$receptor
     numLPattern <- nrow(vecL)
     numRPattern <- nrow(vecR)
-    col.ligand <- brewer.pal(9, "Reds")
-    col.receptor <- brewer.pal(9, "Blues")
+    col.ligand <- .setColor("reds")
+    col.receptor <- .setColor("blues")
     # Clustering
     ClusterL <- t(apply(vecL, 1, .HCLUST))
     ClusterR <- t(apply(vecR, 1, .HCLUST))