paper_figures

1 Functions

2 Data

#read datasets
GBMSeurat_cancer_sipsic_cp = readRDS(".Data/GBMSeurat_cancer_sipsic_cp.RDS")

Warning in gzfile(file, "rb") :
  cannot open compressed file '.Data/GBMSeurat_cancer_sipsic_cp.RDS', probable reason 'No such file or directory'
Error in gzfile(file, "rb") : cannot open the connection

# set clustering to 13 clusters
GBMSeurat_cancer_sipsic_cp <- FindClusters(GBMSeurat_cancer_sipsic_cp, resolution = 0.61)

Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 10000
Number of edges: 360064

Running Louvain algorithm...

0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

Maximum modularity in 10 random starts: 0.8640
Number of communities: 14
Elapsed time: 1 seconds

#set names
GBMSeurat_cancer@project.name = "GBM_original"
GBMSeurat_cancer_sipsic_cp@project.name = "GBM_sipsic_cp"
GBM.combined@project.name = "GBM_seurat_integration"
GBMSeurat_cancer_harmony@project.name = "GBM_harmony"
GBMSeurat_cancer_scvi@project.name = "GBM_scvi"

all_datasets = list(GBMSeurat_cancer,GBMSeurat_cancer_sipsic_cp,GBM.combined,GBMSeurat_cancer_harmony,GBMSeurat_cancer_scvi)

saveRDS(object = GBM.combined,file = "/sci/labs/yotamd/lab_share/avishai.wizel/R_projects/GBM_batch_effect/Data/GBM_seurat_integrated.RDS")
saveRDS(object = GBMSeurat_cancer_harmony,file = "/sci/labs/yotamd/lab_share/avishai.wizel/R_projects/GBM_batch_effect/Data/GBMSeurat_harmony.RDS")
saveRDS(object = GBMSeurat_cancer_scvi,file = "/sci/labs/yotamd/lab_share/avishai.wizel/R_projects/GBM_batch_effect/Data/GBMSeurat_scvi.RDS")
saveRDS(object = GBMSeurat_cancer,file = "/sci/labs/yotamd/lab_share/avishai.wizel/R_projects/GBM_batch_effect/Data/GMB_no_integration.RDS")

3 UMAPS

cell_types_levels <-c( "MesLike1", "MesLike2", "NPCLike1", "NPCLike2", "OPCLike","ACLike")
colors = RColorBrewer::brewer.pal(6, "Paired"); colors[5] = "orange"

all_plots= list()

for (i in seq_along(all_datasets)) {
  dataset = all_datasets[[i]]
  p = DimPlot(dataset, reduction = "umap",group.by = c("seurat_clusters","orig.ident","cancer_type"),ncol = 1)
  p[[3]] = p[[3]] + scale_color_manual(values = colors,limits = cell_types_levels) 
  p[[1]]$labels$title  = dataset@project.name
  p[[2]]$labels$title = NULL
  p[[3]]$labels$title  = NULL
  all_plots[[i]] = p
  
}

umaps_p = patchwork::wrap_plots(all_plots,ncol = 5,guides = "collect")
umaps_p

pdf(width = 19,height = 12,file = "./Figures/all/UMAPs.pdf")
umaps_p
dev.off()

null device 
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4 Stacked barplots

pdf(width = 10,height = 8,file = "./Figures/all/barplots.pdf")
barplots_p
dev.off()

null device 
          1