---
title: "clusterTree"
author: "Luise A. Seeker"
date: "19/07/2021"
output: html_document
---
```{r}
library(clustree)
library(Seurat)
library(ggsci)
```
Pick colour paletts
```{r}
mypal <- pal_npg("nrc", alpha = 0.7)(10)
mypal2 <-pal_tron("legacy", alpha = 0.7)(7)
mypal3 <- pal_lancet("lanonc", alpha = 0.7)(9)
mypal4 <- pal_simpsons(palette = c("springfield"), alpha = 0.7)(16)
mypal5 <- pal_rickandmorty(palette = c("schwifty"), alpha = 0.7)(6)
mypal6 <- pal_futurama(palette = c("planetexpress"), alpha = 0.7)(5)
mypal7 <- pal_startrek(palette = c("uniform"), alpha = 0.7)(5)
mycoloursP<- c(mypal, mypal2, mypal3, mypal4, mypal5, mypal6, mypal7)
```
```{r}
seur_comb <- readRDS("/Users/lseeker/Documents/Work/HumanCellAtlas/srt_annotated_nadine/srt_anno_01.RDS")
nad_ol <- readRDS(here::here("data",
"single_nuc_data",
"oligodendroglia",
"srt_oligos_and_opcs_LS.RDS"))
```
```{r}
DotPlot(nad_ol, features = c("PDGFRA", "PLP1", "PAX3", "SLC22A3", "NELL1", "GAP43",
"GPC5", "GPR17", "PRICKLE1", "SGK1", "OPALIN",
"PLXDC2", "HHIP", "RASGRF1",
"RBFOX1", "AFF3", "FMN1", "SPARC", "HCN2", "TUBB2B")) + RotatedAxis()
```
```{r}
nad_ol@meta.data$ol_clusters_named <- factor(nad_ol@meta.data$ol_clusters_named,
levels = c("Oligo_B",
"Oligo_D",
"Oligo_E",
"Oligo_C",
"Oligo_A",
"Oligo_F",
"OPC_A",
"OPC_B",
"COP_A",
"COP_B",
"COP_C"))
Idents(nad_ol) <- nad_ol@meta.data$ol_clusters_named
DotPlot(nad_ol, features = c("PDGFRA", "PLP1",
"GPR17", "PRICKLE1", "SGK1", "BCAN",
"GPC5", "SPARCL1", "TRPM3", "GRIA1",
"GAP43", "TRIO", "ATRNL1",
"NELL1", "L3MBTL4", "LINC01965",
"PAX3", "SLC22A3", "SEMA3D",
"SPARC", "DHCR24", "HCN2", "TUBA1A", "TUBB2B",
"VAMP3", "PMP2",
"OPALIN","PLXDC2", "LAMA2", "PALM2", "HHIP",
"RBFOX1","FMN1",
"RASGRF1", "AFF3",
"LGALS1")) + RotatedAxis()
```
```{r}
seur_comb <- FindClusters(seur_comb,
resolution = c(0, 0.02, 0.05))
```
```{r, fig.width= 8, fig.height=15}
clustree(
seur_comb,
prefix = "RNA_snn_res.",
exprs = c("data", "counts", "scale.data"),
assay = NULL)
```
```{r}
Idents(seur_comb) <- "RNA_snn_res.1.3"
seur_comb@meta.data$dot_plot_id <- factor(as.factor(seur_comb$RNA_snn_res.1.3),
levels = c("8", "0", "5", "6", "1", "18",
"4", "28", "7", "11", "26",
"10", "27", "21", "15",
"2", "13", "9", "24", "31",
"22", "29", "32", "3",
"30", "14", "17", "23",
"16", "12", "19", "20",
"25"))
Idents(seur_comb) <- "dot_plot_id"
```
```{r}
DotPlot(seur_comb, features = c("GAPDH",
"SNAP25",
"NRG1",
"NEFH",
"SATB2",
"PDGFRA",
"FAM19A1",
"GAD2",
"GRIK1",
"KIT",
"GJA1",
"SHISA6",
"EMID1",
"MTURN",
"DNAH9",
"CD74",
"CXCR4",
"HS3ST4",
"P2RY12",
"RELN",
"CLDN5",
"VWF",
"PDGFRB",
"MAG"))+ RotatedAxis()
```
Add Nadine's cluster labels to my oligodendroglia dataset
```{r}
subs_boul <- colnames(seur_comb) %in% colnames(nad_ol)
nad_md <- seur_comb@meta.data
subs_nad_md <- nad_md[subs_boul, ]
ol_md <- nad_ol@meta.data
test<- subs_nad_md$Barcode == ol_md$Barcode
# Barcodes are in the same order so that I can simply add information to the
# nad_ol Seurat object
nad_ol@meta.data$nad_clusters <- subs_nad_md$clusters_1.3
DimPlot(nad_ol, label = TRUE, cols = mycoloursP[6:40], group.by = "nad_clusters")
```
```{r, fig.width = 10, fig.height = 8}
DimPlot(nad_ol, label = TRUE, cols = mycoloursP[6:40],
group.by = "nad_clusters",
split.by = "nad_clusters",
ncol = 3)
```
```{r}
DimPlot(nad_ol, label = TRUE, cols = mycoloursP[6:40])
```
```{r}
FeaturePlot(nad_ol, features = "VIM")
FeaturePlot(nad_ol, features = "FABP7")
FeaturePlot(nad_ol, features = "TTYH1")
FeaturePlot(nad_ol, features = "SPARCL1")
FeaturePlot(nad_ol, features = "HES1")
FeaturePlot(nad_ol, features = "CLU")
FeaturePlot(nad_ol, features = "FOS")
```
```{r}
FeaturePlot(nad_ol, features = "GFAP")
```
```{r}
FeaturePlot(nad_ol, features = "SOX9")
```
```{r}
FeaturePlot(nad_ol, features = "S100B")
FeaturePlot(nad_ol, features = "KCND2")
FeaturePlot(nad_ol, features = "OLIG1")
FeaturePlot(nad_ol, features = "PCDH15")
FeaturePlot(nad_ol, features = "SCRG1")
FeaturePlot(nad_ol, features = "LHFPL3")
FeaturePlot(nad_ol, features = "OPCML")
FeaturePlot(nad_ol, features = "APOD")
FeaturePlot(nad_ol, features = "OLIG2")
FeaturePlot(nad_ol, features = "NKX2-2")
```
David's paper
```{r}
FeaturePlot(nad_ol, features = "LUZP2")
FeaturePlot(nad_ol, features = "NCALD")
FeaturePlot(nad_ol, features = "NR0B1")
FeaturePlot(nad_ol, features = "ETV1")
FeaturePlot(nad_ol, features = "MITF")
FeaturePlot(nad_ol, features = "TRAF4")
```
```{r}
FeaturePlot(nad_ol, features = "HES1")
FeaturePlot(nad_ol, features = "GLIS3")
FeaturePlot(nad_ol, features = "FOS")
FeaturePlot(nad_ol, features = "NFIA")
FeaturePlot(nad_ol, features = "NFIB")
FeaturePlot(nad_ol, features = "HES4")
FeaturePlot(nad_ol, features = "TSC22D4")
FeaturePlot(nad_ol, features = "NFATC2")
FeaturePlot(nad_ol, features = "JUNB")
FeaturePlot(nad_ol, features = "HES5")
FeaturePlot(nad_ol, features = "FOXJ1")
```
```{r}
FeaturePlot(nad_ol, features = "SPARCL1")
```
```{r}
seur_comb@meta.data$annot_clu <- ifelse(seur_comb@meta.data$clusters_named == "Oligo"|
seur_comb@meta.data$clusters_named == "OPC",
paste(seur_comb@meta.data$clusters_named,
seur_comb@meta.data$clusters_1.3,
sep= "_"),
paste(seur_comb@meta.data$clusters_named))
DimPlot(seur_comb, group.by = "annot_clu", label = TRUE,
cols = c(mycoloursP[17:50])) +NoLegend()
```
```{r}
DimPlot(seur_comb, group.by = "annot_clu", label = FALSE,
cols= c(mycoloursP[17:50], mycoloursP[1:15]),
split.by = "Tissue") +NoLegend()
```
```{r}
Idents(nad_ol) <- "Tissue"
DotPlot(nad_ol, features = c("SKAP2",
"GNA14",
"PLP1",
"NCKAP5",
"LRRC7"
))+ RotatedAxis()
```
```{r}
DimPlot(seur_comb,
cols = c(mycoloursP[10:40], mycoloursP[1:10]),
label = FALSE)
```
```{r}
DimPlot(seur_comb, group.by = "rough_annot", label = FALSE,
cols= c(mycoloursP[17:50], mycoloursP[1:15])) +NoLegend()
```
session info
```{r}
sessionInfo()
```