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Notebook4_E18.5_and_preterm_P0
Laura Wolbeck
2023-02-28

In this notebook DEG and GSEA analysis is performed for samples E 18.5 and preterm P0. Moreover, this script includes code for all figures of E 18.5 and preterm P0 samples. For DEG and GSEA the package "cacoa" was used: https://github.com/kharchenkolab/cacoa/tree/main.

Setup

#Load helper functions
source("scRNA_helper_functions_preterm.R")

#Load libraries
library(conos) #version 1.4.0
library(pagoda2)
library(magrittr)
library(ggplot2)
library(cacoa)
library(xlsx)

1. DEG analysis

Read in high resolution annotation file "anno" Read in con1 from notebook1 as "con"

Create condition factor for cacoa object

condition <- setNames(c("fullterm", "fullterm", "preterm", "preterm"), names(con$samples))

Create Cacoa object

cao <- Cacoa$new(con, cell.groups = anno, sample.groups=condition, n.cores = 10, ref.level = "fullterm", target.level = "preterm")

estimate DE genes

cao$estimatePerCellTypeDE(n.cores=50)  #DEs not calculated for Microglia

save DEG of RG as excel file

DEG <- cao$test.results$de %>% lapply("[[", "res") 
write.xlsx(x = DEG$RG, file= "DEG_early_RG.xlsx")

2. GSEA

cao$estimateOntology(type="GSEA", org.db=org.Mm.eg.db)

save GSEA results of RG as excel file

cao$saveOntologyAsTable("early_GSEA.tsv", name="GSEA")
GSEA <- read.table("early_GSEA.tsv", sep="\t")
write.xlsx(x = GSEA[GSEA$V1=="RG",], file= "GSEA_early_RG.xlsx")

3. Figures

Fig S5B: compositional data analysis

cao$estimateCellLoadings()

cao$plotCellLoadings(signif.threshold=0.05, show.pvals = F) + xlab("separation coefficient") 
ggsave("Compositionshifts_early.pdf",width=6, height=4.5)

Fig S7D

#defining colours of clusters
colours_high <- c("#e1af32","#FFAF32","#3232FF","#32FF32","#FFFF00","#CDCD32","#FF9b9b","#EB8C32","#C8961E","#FF3232","#AF3232","#B49191","#694646","#820000","#965050","#550505","#C80F0F","#AF32FF","#E632E6","#FFC8FF","#DBFF00", "#0096FF") %>% setNames(c("Immature ependymal cells-2","Immature ependymal cells-2","RG","Intermediate progenitor cells","Dividing cells-2","Dividing cells-1","Neuroblasts-1", "Dividing cells-4", "Dividing cells-3","Neuroblasts-2","Neurons 1-1","Neurons 1-2","Neurons 2","Neurons 3-3","Neurons 3-4","Neurons 3-1","Neurons 3-2","OPC","Microglia", "Endothelial/Pericytes/VSMC","Erythrocyte", "MKi67+_RG"))

con$plotGraph(groups=anno, label="") + scale_colour_manual(values=colours_high)+  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

Fig S7E

#define words to exclude from collapsed GO terms
ex_words <- c('regulation', 'process', 'cell')
RG <- cao$plotOntologyHeatmapCollapsed(
  name="GSEA", genes="down", n=70, size.range=c(1, 4), subtype="BP", exclude.words=ex_words, clust.method="ward.D")

#filter for Radial glia
RG$data %<>% filter(G2=="RG", value > 0)

df <- RG$data
df %<>% arrange(value) %>% mutate(G1 = G1 %>% factor(., levels = .))

#define color legend
color.guide <- guide_colorbar(title = "-log10(p-value)", title.position = "left", 
        title.theme = element_text(angle = 90, hjust = 0.5))


ggplot(df, aes(x=G2, y = G1, fill = value)) + geom_tile( colour="white", size=0.2) +  scale_fill_distiller(direction = 1 , palette = "Blues") + guides(fill = color.guide) + labs(title="Top 30 down of RG ", y = " ", x= " ") + theme_grey(base_size = 11) + theme(axis.ticks.x = element_blank(),  axis.text.x = element_blank())

Fig S7F

#define words to exclude from collapsed GO terms
ex_words <- c('regulation', 'process', 'cell')
RG <- cao$plotOntologyHeatmapCollapsed(
  name="GSEA", genes="up", n=100, size.range=c(1, 4), subtype="BP", exclude.words=ex_words, clust.method="ward.D")

RG$data %<>% filter(G2=="RG", value > 0)

#filter for Radial glia
df <- RG$data
df %<>% arrange(value) %>% mutate(G1 = G1 %>% factor(., levels = .))

#define color legend
color.guide <- guide_colorbar(title = "-log10(p-value)", title.position = "left", 
        title.theme = element_text(angle = 90, hjust = 0.5))

ggplot(df, aes(x=G2, y = G1, fill = value)) + geom_tile( colour="white", size=0.2) +  scale_fill_distiller(direction = 1 , palette = "Reds") + guides(fill = color.guide) + labs(title="Top 30 up of RG", y = " ", x= " ") + theme_grey(base_size = 11) + theme(axis.ticks.x = element_blank(),  axis.text.x = element_blank())