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query_genes.R
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query_genes.R
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library(DropletUtils)
library(Seurat, lib.loc = "~/R/x86_64-redhat-linux-gnu-library/3.6/")
library(tidyverse)
library(wesanderson)
library(reshape2)
library(RColorBrewer)
library(grid)
library(gridExtra)
library(cowplot) #moo
library(devtools)
library(beyonce, lib.loc = "/volumes/lab/users/aschalck/R/")
library(ggalluvial)
require(foreign)
require(nnet)
library(lme4)
library(GGally)
library(fgsea)
library(future)
library(future.apply)
library(tidyverse)
library(fuzzyjoin)
library(quantreg)
source("~/TENX/analysis/MP/MP_project_4/TCR_functions_script.R")
options(future.globals.maxSize = 60000 * 1024^2)
NewSet1 = function(n){return(colorRampPalette(brewer.pal(9,"Set1")[c(1,5,6,3,2,4,8,7,9)])(n))}
library(ComplexHeatmap)
VlnPlot(SCTall_fil2, group.by = "minor_clusters2",
split.by = "timepoint", split.plot = T, col=treatment_colors,
pt.size = 0, features = c("rad_resp.1"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("IL18"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("IL1B"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("IL33"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("NLRP3"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("TNFRSF1A"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("IL1R1"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("TNFRSF1B"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("MYD88"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("IRAK2"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("GSDMD"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("KCNK6"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("CASP4"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("CASP5"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("TLR3"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("TICAM1"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("JUN"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("NFKB1"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("NFKB2"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("TLR4"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("MYD88"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("CXCL8"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("MMP9"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("HIF1A"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("NFKBIA"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("TLR2"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("TLR3"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("TLR1"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("TLR4"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, features = c("IFNG"))
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0,
features = c(paste0("TLR",1:10)), ncol = 5)
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0,
features = c("CXCL8"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0,
features = c("IL13"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("sct_IFNG"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0,
features = c("CD80"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IL1R1"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IL1RAP"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("NFKBIA"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IL1RL1"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IL4"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IL5"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("EOMES"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("TBX21"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("RORC"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("GATA3"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("MX1"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("OAS1"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IRF1"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("SIN3A"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("ISG15"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("STAT2"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("STAT1"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("STAT3"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IFNGR1"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("TNF"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IFNGR2"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IFNAR1"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IFNAR2"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IRF1"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IL4","IL5","IL9","IL13"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("sct_IFNG"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("CD40LG"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("FASLG"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
pt.size = 0, assay = "SCT",slot = "data",
features = c("TNF","sct_IFNG","IL2"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
pt.size = 0, assay = "SCT",slot = "data",
features = c("ITGAE","EOMES","TIGIT","ENTPD1","CTLA4","PDCD1","TOX"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
pt.size = 0, assay = "SCT",slot = "data",
features = c("LAYN","TOX","ID2","HIF1A","ZEB2","TBX21"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
pt.size = 0, assay = "SCT",slot = "data",
features = c("GZMA","GZMK","GNLY","GZMB"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
pt.size = 0, assay = "SCT",slot = "data",
features = c("GATA3","IL4","IL10","RORGT"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("CD69"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
pt.size = 0, assay = "SCT",slot = "data",
features = c("CD69"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
pt.size = 0, assay = "SCT",slot = "data",
features = c("IL2RA"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
pt.size = 0, assay = "SCT",slot = "data",
features = c("LAG3"))
VlnPlot(SCTall_fil2_epi, group.by = "patient", split.plot = T,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("S.Score","G2M.Score") ,cols = treatment_colors)
VlnPlot(SCTall_fil2, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IL5"))
VlnPlot(SCTall_fil2, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IL4"))
VlnPlot(SCTall_fil2, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IL13"))
VlnPlot(SCTall_fil2, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IL1B"))
VlnPlot(SCTall_fil2, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IL18"))
VlnPlot(SCTall_fil2, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("IL33"))
VlnPlot(SCTall_fil2, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("TGFB1"))
VlnPlot(SCTall_fil2, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("RNASEH2A"))
VlnPlot(SCTall_fil2, group.by = "patient",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("CD68"))
VlnPlot(SCTall_fil2, group.by = "major_clusters",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("HLA-A"))
SCTall_fil2 = AddModuleScore(SCTall_fil2, features = ISGs, name = "ISGs")
VlnPlot(SCTall_fil2, group.by = "major_clusters",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("ISGs1"))
VlnPlot(SCTall_fil2, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("ISGs1"))
VlnPlot(SCTall_fil2, group.by = "minor_clusters2",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("LIG1"))
#saveRDS(SCTall_fil2_epi, file = "./Rda/tumor_RNA.rds", compress = FALSE)
VlnPlot(SCTall_fil2_tcells, group.by = "patient",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("CCL4L2","CCL4"),
split.plot = TRUE, cols = rev(treatment_colors))
VlnPlot(SCTall_fil2_epi, group.by = "patient",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("NR4A1","ZFP36"),
split.plot = TRUE, cols = rev(treatment_colors))
VlnPlot(SCTall_fil2_epi, group.by = "patient",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = BCR15_epi_post_markers_top, ncol = 5,
split.plot = TRUE, cols = rev(treatment_colors))
VlnPlot(SCTall_fil2_epi, group.by = "patient",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("PRKCZ"),
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2, group.by = "major_clusters",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("PRKCZ"),
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2_epi, group.by = "patient", ncol = 2,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("HLA-A","HLA-B","HLA-C","B2M"),
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2_myeloid, group.by = "patient", ncol = 2,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("HLA-A","HLA-B","HLA-C","B2M"),
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2_epi, group.by = "patient", ncol = 2,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("HLA-A","HLA-B","HLA-C","B2M"),
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2, group.by = "major_clusters", ncol = 2,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("HLA-A","HLA-B","HLA-C","B2M"),
split.plot = TRUE, cols = treatment_colors)
SCTall_fil2_epi = AddModuleScore(SCTall_fil2_epi, features = list(c("HLA-A","HLA-B","HLA-C","B2M")), name = "HLA.")
VlnPlot(SCTall_fil2_epi, group.by = "patient", ncol = 1,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = "HLA.1",
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2_epi, group.by = "patient", ncol = 2,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("CD274","CDK4","CDK6"),
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2, group.by = "major_clusters", ncol = 2,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = c("CD274","CDK4","CDK6"),
split.plot = TRUE, cols = treatment_colors)
checkpoint_genes = c("TNFRSF14","TNFSF18","CD80","CD86","PVR","CD274","PDCD1LG2","LGALS9","CD40","TNFSF4","TNFSF9","ICOSLG","CD70")
checkpoint_tcells = c("BTLA","TNFRSF18","CTLA4","TIGIT","PDCD1","HAVCR2","LAG3","CD28","CD40LG","TNFRSF4","TNFRSF9","ICOS","CD27")
VlnPlot(SCTall_fil2_epi, group.by = "patient", ncol = 4,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = checkpoint_genes,
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2_epi, group.by = "patient", ncol = 4,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = "PDCD1",
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2_myeloid, group.by = "patient", ncol = 4,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = checkpoint_genes,
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2_myeloid, group.by = "minor_clusters2", ncol = 2,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = checkpoint_genes[c(1,4,8,9)],
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2_tcells, group.by = "patient", ncol = 4,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = checkpoint_tcells,
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4", ncol = 4,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = checkpoint_tcells,
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
pt.size = 0, assay = "SCT",slot = "data",
features = "BCL6")
tcga_bc_genes = pull(read_tsv("/volumes/seq/database/CancerGenes/TCGA_breastCancer_genelist_45.txt", col_names = "gene"))
VlnPlot(SCTall_fil2[,SCTall_fil2$minor_clusters2 %in% tumor_clusters], group.by = "patient", ncol = 10,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = tcga_bc_genes,
split.plot = TRUE, cols = treatment_colors) -> temp
ggsave(temp, filename = "~/TENX/analysis/BCR/BCR_4/plots/plots11/BC_tcga_genes_vln.png", width = 30, height = 15)
BC_bed_genes = pull(read_tsv("~/code/resources/gene_lists/BC_genes.sorted.bed", col_names = F), "X4")
VlnPlot(SCTall_fil2[,SCTall_fil2$minor_clusters2 %in% tumor_clusters], group.by = "patient", ncol = 10,
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = BC_bed_genes,
split.plot = TRUE, cols = treatment_colors) -> temp
ggsave(temp, filename = "~/TENX/analysis/BCR/BCR_4/plots/plots11/BC_bed_genes_vln.png", width = 30, height = 25)
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
pt.size = 0, assay = "SCT",slot = "data",
features = c("ENTPD1","PDCD1","ITGAE"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
pt.size = 0, assay = "SCT",slot = "data",
features = c("CX3CR1","FGFBP2","FCGR3A"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
pt.size = 0, assay = "SCT",slot = "data",
features = c("sct_IFNG","TNF"))
SCTall_fil2_tcells$PD1 = c("-","+")[as.numeric(SCTall_fil2_tcells@assays$RNA@counts["PDCD1",] > 0) + 1]
SCTall_fil2_tcells@meta.data %>%
ggplot() + aes(x=patient, fill=PD1) +
geom_bar(position="fill") + theme(axis.text.x = element_text(angle = 90)) +
facet_wrap(~timepoint)
VlnPlot(SCTall_fil2_tcells, group.by = "patient",split.by = "timepoint",
pt.size = 0, assay = "SCT",slot = "data",split.plot = T,
features = c("ENTPD1","PDCD1","ITGAE"))
VlnPlot(SCTall_fil2_tcells, group.by = "patient",split.by = "timepoint",
pt.size = 0, assay = "SCT",slot = "data",split.plot = T,
features = c("CX3CR1","FGFBP2","FCGR3A"))
VlnPlot(SCTall_fil2_tcells, group.by = "minor_clusters4",
pt.size = 0, assay = "SCT",slot = "data",
features = "BCL6")
pro_apop_genes = c("BCL2L11","BID","BAD","BMF","BBC3","PMAIP1","BAK1","BAX","BOK")
anti_apop_genes = c("MCL1","BCL2","BCL2L1","BCL2L2","BCL2A1")
VlnPlot(SCTall_fil2[,SCTall_fil2$minor_clusters2 %in% tumor_clusters], group.by = "patient",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = pro_apop_genes,
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2[,SCTall_fil2$minor_clusters2 %in% tumor_clusters], group.by = "patient",
split.by = "timepoint", pt.size = 0, assay = "SCT",slot = "data",
features = anti_apop_genes,
split.plot = TRUE, cols = treatment_colors)
VlnPlot(SCTall_fil2, group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
features = pro_apop_genes)
VlnPlot(SCTall_fil2, group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",split.by = "timepoint",
features = "GLB1")
SCTall_fil2 = AddModuleScore(SCTall_fil2, features = list(pro_apop_genes), name = "pro.apop.")
SCTall_fil2 = AddModuleScore(SCTall_fil2, features = list(anti_apop_genes), name = "anti.apop.")
VlnPlot(SCTall_fil2[,SCTall_fil2$minor_clusters2 %in% tumor_clusters],
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "pro.apop.1") + NoLegend()
VlnPlot(SCTall_fil2[,SCTall_fil2$minor_clusters2 %in% tumor_clusters],
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "anti.apop.1") + NoLegend()
SCTall_fil2_epi = AddModuleScore(SCTall_fil2_epi, features = list(pro_apop_genes), name = "pro.apop.")
SCTall_fil2_epi = AddModuleScore(SCTall_fil2_epi, features = list(anti_apop_genes), name = "anti.apop.")
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "pro.apop.1") + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "anti.apop.1") + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = anti_apop_genes) + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = pro_apop_genes) + NoLegend()
VlnPlot(SCTall_fil2,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "MCL1") + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "NFKB1") + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "PITPNM3") + NoLegend()
atm, atr, dnapcs
SCTall_fil2_epi = AddModuleScore(SCTall_fil2_epi, features = list(pro_apop_genes), name = "pro.apop.")
DAS_genes = c("CDKN2A","HMGA1","HMGA2","HIRA","ASF1A","H2AFY","H2AFY2","PML","MMP3","TP53BP1","CDKN1A")
SCTall_fil2_epi = AddModuleScore(SCTall_fil2_epi, features = list(DAS_genes), name = "pro.DAS.")
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = DAS_genes) + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "pro.DAS.1") + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "SLCO2B1") + NoLegend()
HLA_genes = sort(row.names(SCTall_fil2_macs)[str_detect(row.names(SCTall_fil2_macs), "^HLA-")])
HLA_2_genes = c(HLA_genes[str_detect(HLA_genes, "^HLA-[D]")],"CD74")
VlnPlot(SCTall_fil2_macs,
group.by = "major_clusters",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = HLA_2_genes) + NoLegend()
VlnPlot(SCTall_fil2[,SCTall_fil2$major_clusters == "Myeloid"],
group.by = "major_clusters",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = HLA_2_genes) + NoLegend()
VlnPlot(SCTall_fil2,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "CD68") + NoLegend()
VlnPlot(SCTall_fil2,
group.by = "patient",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "CD68") + NoLegend()
SCTall_fil2_macs = AddModuleScore(SCTall_fil2_macs, features = list(HLA_2_genes[c(1,2,3,5,6,7,9,12,13,14,15)]), name = "HLA.II.", nbin = 15)
VlnPlot(SCTall_fil2_macs,
group.by = "patient",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "HLA.II.1") + NoLegend()
for(i in patients){
pre = SCTall_fil2_macs$HLA.II.1[SCTall_fil2_macs$patient == i & SCTall_fil2_macs$timepoint == "pre"]
post = SCTall_fil2_macs$HLA.II.1[SCTall_fil2_macs$patient == i & SCTall_fil2_macs$timepoint == "post"]
data.frame(score = pre, timepoint="pre") %>%
rbind( data.frame(score = post, timepoint="post")) %>%
ggplot(aes(x=score, color = timepoint, fill = NULL)) +
geom_boxplot() + coord_flip() + theme_minimal() + ggtitle(i) -> g
print(g)
p = wilcox.test(pre, post)$p.value
print(i)
print(p)
}
SCTall_fil2 = AddModuleScore(SCTall_fil2, features = list(HLA_2_genes[c(1,2,3,5,6,7,9,12,13,14,15)]), name = "HLA.II.", nbin = 15)
VlnPlot(SCTall_fil2,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "HLA.II.1") + NoLegend()
for(i in patients){
pre = SCTall_fil2$HLA.II.1[SCTall_fil2$patient == i & SCTall_fil2$timepoint == "pre" & str_detect(SCTall_fil2$minor_clusters2 , "Macro|Dend")]
post = SCTall_fil2$HLA.II.1[SCTall_fil2$patient == i & SCTall_fil2$timepoint == "post" & str_detect(SCTall_fil2$minor_clusters2 , "Macro|Dend")]
print(g)
p = wilcox.test(pre, post)$p.value
print(i)
print(p)
}
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = c( "CEP55", "MCM7", "CDC45", "MCM5", "KIF18B"," CIT", "EZH2")) + NoLegend()
SCTall_fil2_epi = AddModuleScore(SCTall_fil2_epi, features = list(sgs), name = "sen.")
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "sen.1") + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = sgs[1:16]) + NoLegend()
C2_df = msigdbr(species = "Homo sapiens", category = "C2")
C2_df %>%
filter(gs_id %in% c("M9143")) %>%
filter(gene_symbol %in% row.names(SCTall_fil2_epi)) %>%
pull(gene_symbol) ->
temp
temp = temp[rowSums(SCTall_fil2_epi[temp,]) > 5000]
SCTall_fil2_epi = AddModuleScore(SCTall_fil2_epi, features = list(temp), name = "M9143.")
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "M9143.1") + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = temp[1:16]) + NoLegend()
so = SCTall_fil2_epi
gsea_df = C2_df
path.id = "M27188"
n=5000
module_plot = function(so, gsea_df, path.id, n, clus = "minor_clusters2", split = "timepoint"){
gsea_df %>%
filter(gs_id %in% path.id) %>%
filter(gene_symbol %in% row.names(so)) %>%
pull(gene_symbol) ->
temp
temp = temp[rowSums(so[temp,]) >= n]
so = AddModuleScore(so, features = list(temp), name = paste0(path.id,"."))
plotlist = list()
p = VlnPlot(so,
group.by = clus,
pt.size = 0, assay = "SCT",slot = "data",
split.by = split,split.plot = T,
features = paste0(path.id,".1")) + NoLegend()
plotlist[["score"]] = p
for(i in temp){
plotlist[[i]] = VlnPlot(so,
group.by = clus,
pt.size = 0, assay = "SCT",slot = "data",
split.by = split,split.plot = T,
features = i) + NoLegend()
}
return(plotlist)
}
genes = c("PVRL4","GPR172B","DAO","CCDC74B")
custom_module_plot = function(so, genes, n, clus = "minor_clusters2", split = "timepoint"){
print(genes[!genes %in% row.names(so)])
temp = genes[genes %in% row.names(so)]
temp = temp[rowSums(so[temp,]) >= n]
so = AddModuleScore(so, features = list(temp), name = "score.")
plotlist = list()
p = VlnPlot(so,
group.by = clus,
pt.size = 0, assay = "SCT",slot = "data",
split.by = split,split.plot = T,
features = "score.1") + NoLegend()
plotlist[["score"]] = p
for(i in temp){
plotlist[[i]] = VlnPlot(so,
group.by = clus,
pt.size = 0, assay = "SCT",slot = "data",
split.by = split,split.plot = T,
features = i) + NoLegend()
}
return(plotlist)
}
vln_sen_M27188 = module_plot(SCTall_fil2_epi, gsea_df, "M27188",5000)
vln_sen_M9143 = module_plot(SCTall_fil2_epi, gsea_df, "M9143",5000)
vln_sen_M27189 = module_plot(SCTall_fil2_epi, gsea_df, "M27189",5000)
vln_sen_M27191 = module_plot(SCTall_fil2_epi, gsea_df, "M27191",5000)
vln_sen_M27190 = module_plot(SCTall_fil2_epi, gsea_df, "M27190",5000)
vln_sen_M27187 = module_plot(SCTall_fil2_epi, gsea_df, "M27187",1000)
nagano_1 = c("NECTIN4","SLC52A1","DAO","CCDC74B","LOXL4","EVL","PRODH","E2F7","LY6D","IGFBP2","CRABP2","EPN3","APOBEC3B","IER5","ANGPTL2","SLC48A1","METTL27","E2F2","NXPH4","PPM1D","CDKN1A","BTG2","SULF2")
vln_nagano_1 = custom_module_plot(SCTall_fil2_epi, nagano_1,500)
nagano_3 = c("NECTIN4","PRODH","LY6D","DAO","EPN3","SLC52A1")
nagano_2 = c("NECTIN4","CDKN1A","IGFBP2","E2F7","SLC48A1","APOBEC3B","IER5","E2F2","LOXL4")
vln_nagano_2 = custom_module_plot(SCTall_fil2_epi, nagano_2,500)
vln_nagano_3 = custom_module_plot(SCTall_fil2_epi, nagano_3,100)
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "CDKN2B") + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,
features = "FOXM1") + NoLegend()
DotPlot(SCTall_fil2_epi, assay = "SCT", features = c("FOXM1","FOS","JUN"), split.by = "timepoint", cols = c("red","blue"))
tumor_prepost_df %>%
filter(gene %in% tfs) %>%
arrange(patient, -avg_logFC) %>%
filter(cluster=="post") %>%
filter(avg_logFC > 0) %>%
mutate(pct.dif = pct.1-pct.2) %>%
group_by(gene) %>%
summarise(m = mean(avg_logFC), pct = mean(pct.dif)) %>% View()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",adjust = 1,
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,cols = treatment_colors,
features = c("PIK3CA")) + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",adjust = 1,
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,cols = treatment_colors,
features = c("PTK2","ERBB2")) + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",adjust = 1,
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,cols = treatment_colors,
features = c("ESR1")) + NoLegend()
mtor_genes = c("HIF1A", "NFE2L2", "HSF1", "NFAT5", "TP53", "FOXO3")
mtor_genes %in% row.names(SCTall_fil2_epi)
SCTall_fil2_epi = AddModuleScore(SCTall_fil2_epi, features = list(mtor_genes), name = "mtor.")
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,cols = treatment_colors,
features = mtor_genes) + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,cols = treatment_colors,
features = "mtor.1") + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,cols = treatment_colors,
features = mtor_genes) + NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,cols = treatment_colors,
features = tumor_post_avg_top[1:6]) + NoLegend()
FOXO3A_targets = read_tsv("./data/gene_lists/FOXO3A_motifs.txt", skip = 2, col_names = "gene") %>% pull(gene)
FOXO3A_targets = FOXO3A_targets[FOXO3A_targets %in% row.names(SCTall_fil2_epi)]
temp = sort(rowSums(SCTall_fil2_epi@assays$RNA@counts[FOXO3A_targets,]), decreasing = T)
#FOXO3A_targets_high = names(temp[temp >= 5000])
FOXO3A_targets_high = FOXO3A_targets[FOXO3A_targets %in% SCTall_fil2_epi@assays$SCT@var.features]
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,cols = treatment_colors,
features = FOXO3A_targets_high[1:6]) + NoLegend()
SCTall_fil2_epi = AddModuleScore(SCTall_fil2_epi, features = list(FOXO3A_targets_high), name = "foxo3.top.")
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,cols = treatment_colors,
features = "foxo3.top.1") + NoLegend()
p53_targets = read_tsv("./data/gene_lists/p53_motifs.txt", skip = 2, col_names = "gene") %>% pull(gene)
p53_targets = p53_targets[p53_targets %in% row.names(SCTall_fil2_epi)]
temp = sort(rowSums(SCTall_fil2_epi@assays$RNA@counts[p53_targets,]), decreasing = T)
#p53_targets_high = names(temp[temp >= 5000])
p53_targets_high = p53_targets[p53_targets %in% SCTall_fil2_epi@assays$SCT@var.features]
SCTall_fil2_epi = AddModuleScore(SCTall_fil2_epi, features = list(p53_targets_high), name = "p53.top.")
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,cols = treatment_colors,
features = "p53.top.1") + NoLegend()
mdm2_genes = read_tsv("./data/gene_lists/mdm2_genes.txt", skip = 2, col_names = "gene") %>% pull(gene)
mdm2_genes = mdm2_genes[mdm2_genes %in% row.names(SCTall_fil2_epi)]
temp = sort(rowSums(SCTall_fil2_epi@assays$RNA@counts[mdm2_genes,]), decreasing = T)
#mdm2_genes_high = names(temp[temp >= 5000])
mdm2_genes_high = mdm2_genes[mdm2_genes %in% SCTall_fil2_epi@assays$SCT@var.features]
SCTall_fil2_epi = AddModuleScore(SCTall_fil2_epi, features = list(mdm2_genes_high), name = "mdm2.top.")
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,cols = treatment_colors,
features = "mdm2.top.1") + NoLegend()
p300_targets = read_tsv("./data/gene_lists/p300_motifs.txt", skip = 2, col_names = "gene") %>% pull(gene)
p300_targets = p300_targets[p300_targets %in% row.names(SCTall_fil2_epi)]
temp = sort(rowSums(SCTall_fil2_epi@assays$RNA@counts[p300_targets,]), decreasing = T)
#p300_targets_high = names(temp[temp >= 5000])
p300_targets_high = p300_targets[p300_targets %in% SCTall_fil2_epi@assays$SCT@var.features]
SCTall_fil2_epi = AddModuleScore(SCTall_fil2_epi, features = list(p300_targets_high), name = "p300.top.")
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,cols = treatment_colors,
features = c("p300.top.1","mdm2.top.1","p53.top.1","foxo3.top.1","mtor.1")) +
NoLegend()
VlnPlot(SCTall_fil2_epi,
group.by = "minor_clusters2",
pt.size = 0, assay = "SCT",slot = "data",
split.by = "timepoint",split.plot = T,cols = treatment_colors,
features = c("PARP1","NFKBIA","TNF")) +