zhanghao-njmu · zhanghao-njmu · Aug 29, 2023 · Aug 28, 2023 · Aug 28, 2023 · Aug 28, 2023
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: SCP
 Type: Package
 Title: Single Cell Pipeline
-Version: 0.4.8
+Version: 0.5.1
 Author: Hao Zhang
 Maintainer: Hao Zhang <[email protected]>
 Description: SCP provides a comprehensive set of tools for single cell data processing and downstream analysis.
@@ -11,7 +11,7 @@ LazyData: True
 LazyDataCompression: xz
 Depends:
     R (>= 4.1.0)
-biocViews: SingleCell, Visualization
+biocViews: SingleCell, GeneExpression, SingleCellWorkflow, Visualization, ShinyApps
 Imports:
     AnnotationDbi,
     BiocParallel,
@@ -25,6 +25,7 @@ Imports:
     ggplot2 (>= 3.4.0),
     ggtree (>= 3.6.1),
     ggrepel,
+    ggforce,
     GO.db,
     GOSemSim,
     grDevices,
@@ -63,6 +64,7 @@ Remotes:
     YuLab-SMU/ggtree
 Suggests:
     AUCell,
+    concaveman,
     covr,
     destiny,
     devtools,

diff --git a/NAMESPACE b/NAMESPACE
@@ -1,8 +1,10 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(RunDM,Neighbor)
 S3method(RunDM,Seurat)
-S3method(RunDM,dist)
 S3method(RunDM,matrix)
+S3method(RunFR,Seurat)
+S3method(RunFR,default)
 S3method(RunGLMPCA,Assay)
 S3method(RunGLMPCA,Seurat)
 S3method(RunGLMPCA,default)
@@ -80,6 +82,7 @@ export(RunDoubletCalling)
 export(RunDynamicEnrichment)
 export(RunDynamicFeatures)
 export(RunEnrichment)
+export(RunFR)
 export(RunGLMPCA)
 export(RunGSEA)
 export(RunHarmony2)
@@ -298,6 +301,7 @@ importFrom(dplyr,across)
 importFrom(dplyr,all_of)
 importFrom(dplyr,arrange)
 importFrom(dplyr,arrange_at)
+importFrom(dplyr,bind_rows)
 importFrom(dplyr,case_when)
 importFrom(dplyr,desc)
 importFrom(dplyr,distinct)
@@ -308,12 +312,16 @@ importFrom(dplyr,mutate)
 importFrom(dplyr,n)
 importFrom(dplyr,pull)
 importFrom(dplyr,reframe)
+importFrom(dplyr,slice_head)
 importFrom(dplyr,summarise)
 importFrom(dplyr,summarise_at)
+importFrom(ggforce,geom_mark_ellipse)
+importFrom(ggforce,geom_mark_hull)
 importFrom(ggnewscale,new_scale)
 importFrom(ggnewscale,new_scale_color)
 importFrom(ggnewscale,new_scale_fill)
 importFrom(ggplot2,"%+replace%")
+importFrom(ggplot2,.pt)
 importFrom(ggplot2,aes)
 importFrom(ggplot2,after_stat)
 importFrom(ggplot2,alpha)
@@ -322,6 +330,7 @@ importFrom(ggplot2,annotation_custom)
 importFrom(ggplot2,coord_cartesian)
 importFrom(ggplot2,coord_flip)
 importFrom(ggplot2,coord_polar)
+importFrom(ggplot2,draw_key_point)
 importFrom(ggplot2,element_blank)
 importFrom(ggplot2,element_line)
 importFrom(ggplot2,element_rect)
@@ -341,6 +350,7 @@ importFrom(ggplot2,geom_curve)
 importFrom(ggplot2,geom_density_2d)
 importFrom(ggplot2,geom_hex)
 importFrom(ggplot2,geom_hline)
+importFrom(ggplot2,geom_label)
 importFrom(ggplot2,geom_line)
 importFrom(ggplot2,geom_linerange)
 importFrom(ggplot2,geom_path)
@@ -391,6 +401,7 @@ importFrom(ggplot2,scale_fill_gradient)
 importFrom(ggplot2,scale_fill_gradientn)
 importFrom(ggplot2,scale_fill_identity)
 importFrom(ggplot2,scale_fill_manual)
+importFrom(ggplot2,scale_linewidth)
 importFrom(ggplot2,scale_linewidth_continuous)
 importFrom(ggplot2,scale_shape_identity)
 importFrom(ggplot2,scale_size)
@@ -455,8 +466,31 @@ importFrom(gtable,gtable_add_padding)
 importFrom(gtable,gtable_add_rows)
 importFrom(gtable,gtable_col)
 importFrom(gtable,is.gtable)
+importFrom(igraph,V)
 importFrom(igraph,as_adjacency_matrix)
 importFrom(igraph,as_data_frame)
+importFrom(igraph,cluster_fast_greedy)
+importFrom(igraph,cluster_fluid_communities)
+importFrom(igraph,cluster_infomap)
+importFrom(igraph,cluster_leiden)
+importFrom(igraph,cluster_louvain)
+importFrom(igraph,cluster_spinglass)
+importFrom(igraph,cluster_walktrap)
+importFrom(igraph,degree)
+importFrom(igraph,graph_from_adjacency_matrix)
+importFrom(igraph,graph_from_data_frame)
+importFrom(igraph,layout_as_tree)
+importFrom(igraph,layout_in_circle)
+importFrom(igraph,layout_on_grid)
+importFrom(igraph,layout_with_dh)
+importFrom(igraph,layout_with_drl)
+importFrom(igraph,layout_with_fr)
+importFrom(igraph,layout_with_gem)
+importFrom(igraph,layout_with_graphopt)
+importFrom(igraph,layout_with_kk)
+importFrom(igraph,layout_with_lgl)
+importFrom(igraph,layout_with_mds)
+importFrom(igraph,neighbors)
 importFrom(methods,"slot<-")
 importFrom(methods,as)
 importFrom(methods,getFunction)

diff --git a/R/SCP-analysis.R b/R/SCP-analysis.R
diff --git a/R/SCP-app.R b/R/SCP-app.R
@@ -1427,7 +1427,7 @@ server <- function(input, output, session) {
         # print(">>> plot:")
         # print(system.time(
         p2_dim <- SCP::FeatureDimPlot(
-          srt = srt_tmp, features = features2, split.by = split2, reduction = reduction2, slot = slots2, raster = raster2,
+          srt = srt_tmp, features = features2, split.by = split2, reduction = reduction2, slot = "data", raster = raster2,
           calculate_coexp = ifelse(coExp2 == "Yes", TRUE, FALSE), palette = palette2, theme_use = theme2,
           ncol = ncol2, byrow = ifelse(arrange2 == "Row", TRUE, FALSE), force = TRUE
         )
@@ -1647,7 +1647,7 @@ server <- function(input, output, session) {
         # print(">>> plot:")
         # print(system.time(
         p4 <- SCP::FeatureStatPlot(
-          srt = srt_tmp, stat.by = features4, group.by = group4, split.by = split4, plot_type = plottype4,
+          srt = srt_tmp, stat.by = features4, group.by = group4, split.by = split4, slot = "data", plot_type = plottype4,
           calculate_coexp = ifelse(coExp4 == "Yes", TRUE, FALSE), palette = palette4,
           aspect.ratio = 6 / max(length(unique(srt_tmp[[group4, drop = TRUE]])), 1),
           ncol = ncol4, byrow = ifelse(arrange4 == "Row", TRUE, FALSE), force = TRUE

diff --git a/R/SCP-cell_annotation.R b/R/SCP-cell_annotation.R
@@ -177,7 +177,7 @@ RunKNNPredict <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
       features <- features_query
     }
     features_common <- intersect(features, rownames(bulk_ref))
-    message("Use ", length(features_common), " common features to calculate distance.")
+    message("Use ", length(features_common), " features to calculate distance.")
     ref <- t(bulk_ref[features_common, , drop = FALSE])
   } else if (!is.null(srt_ref)) {
     ref_assay <- ref_assay %||% DefaultAssay(srt_ref)
@@ -262,7 +262,7 @@ RunKNNPredict <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
         features <- intersect(features_ref, features_query)
       }
       features_common <- Reduce(intersect, list(features, rownames(srt_query[[query_assay]]), rownames(srt_ref[[ref_assay]])))
-      message("Use ", length(features_common), " common features to calculate distance.")
+      message("Use ", length(features_common), " features to calculate distance.")
       if (isTRUE(ref_collapsing)) {
         ref <- AverageExpression(object = srt_ref, features = features_common, slot = "data", assays = ref_assay, group.by = "ref_group", verbose = FALSE)[[1]]
         ref <- t(log1p(ref))
@@ -339,10 +339,10 @@ RunKNNPredict <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
   #
 
   if (is.null(nn_method)) {
-    if (as.numeric(nrow(query)) * as.numeric(nrow(ref)) < 1e9) {
-      nn_method <- "raw"
-    } else {
+    if (as.numeric(nrow(query)) * as.numeric(nrow(ref)) >= 1e8) {
       nn_method <- "annoy"
+    } else {
+      nn_method <- "raw"
     }
   }
   message("Use '", nn_method, "' method to find neighbors.")