9 IAV Kegg Pathway Candidate Gene Analysis
9.2 Data
t_postfilter <- read.table("Output Files/txome_female_edgeR_postfilter.txt")
t_acute <- read.csv("Output Files/txome_female_edgeR_DEG_acute.csv", row.names=1)
t_peak <- read.csv("Output Files/txome_female_edgeR_DEG_peak.csv", row.names=1)
t_late <- read.csv("Output Files/txome_female_edgeR_DEG_late.csv", row.names=1)
g_postfilter <- read.table("Output Files/gnome_female_edgeR_postfilter.txt")
g_acute <- read.csv("Output Files/gnome_female_edgeR_DEG_acute.csv", row.names=1)
g_peak <- read.csv("Output Files/gnome_female_edgeR_DEG_peak.csv", row.names=1)
g_late <- read.csv("Output Files/gnome_female_edgeR_DEG_late.csv", row.names=1)
t_virus_postfilter <- read.table("Output Files/txome_female_edgeR_viralRNA_postfilter.txt")
t_virus_degs <- read.csv("Output Files/txome_female_edgeR_viralRNA_DEG.csv", row.names=1)
g_virus_postfilter <- read.table("Output Files/gnome_female_edgeR_viralRNA_postfilter.txt")
g_virus_degs <- read.csv("Output Files/gnome_female_edgeR_viralRNA_DEG.csv", row.names=1)
9.4 Overlap with Gene Lists
9.4.2 Differentially Expressed Genes
acute <-
data.frame(
genes=c(intersect(iav$Symbol, t_acute$gene),
intersect(iav$Symbol, g_acute$gene)),
category="acute")
peak <-
data.frame(
genes=c(intersect(iav$Symbol, t_peak$gene),
intersect(iav$Symbol, g_peak$gene)),
category="peak")
late <-
data.frame(
genes=c(intersect(iav$Symbol, t_late$gene),
intersect(iav$Symbol, g_late$gene)),
category="late") %>%
filter(!duplicated(genes))
virus <-
data.frame(
genes=c(intersect(iav$Symbol, t_virus_degs$gene),
intersect(iav$Symbol, g_virus_degs$gene)),
category="virus") %>%
filter(!duplicated(genes))
9.4.3 Compile gene IDs
deg <-
rbind(acute, peak, late, virus) %>%
mutate(id = paste0("hsa:", ifelse(genes %in% iav$Symbol,
iav[match(genes, iav$Symbol),1],
genes)))
expressed <-
data.frame(genes=iav_postfilter) %>%
filter(!genes %in% deg$genes) %>%
mutate(id = paste0("hsa:", ifelse(genes %in% iav$Symbol,
iav[match(genes, iav$Symbol),1],
genes)))
notexpressed <-
data.frame(iav) %>%
filter(!Symbol %in% expressed$genes) %>%
filter(!Symbol %in% deg$genes) %>%
mutate(id = paste0("hsa:", ifelse(Symbol %in% iav$Symbol,
iav[match(Symbol, iav$Symbol),1],
Symbol)))
9.5 Plot pathway map
** no longer used - cannot figure out coloring for some genes. Created map online.
graph_info <-
pathway("hsa05164") %>%
activate(nodes) %>%
mutate(convert_hsa=convert_id("hsa"),
convert_map=convert_id("pathway"),
bgcolor=ifelse(convert_hsa %in% expressed$id, "#ffffe0",
ifelse(convert_hsa %in% deg$id, "#fbc69d", "white")))
graph <-
ggraph(graph_info, x=x, y=y) +
geom_node_rect(aes(filter=type=="gene",
fill=I(bgcolor)),
color="black") +
overlay_raw_map() +
theme_void()
graph
#ggkeggsave(filename="Figures/iavkegg.jpg", graph, dpi=300)
9.5.1 Create Legend
png(filename="Figures/iavkeggleg.png", width = 6, height=7, units="in", res=300)
plot(NULL ,xaxt='n',yaxt='n',bty='n',ylab='',xlab='', , xlim=c(0,100), ylim=c(0,10))
legend("topleft",
legend =c("Acute", "Peak", "Late", "Virus", "Expressed", "Not Expressed"),
pch=15, pt.cex=7, cex=3, bty='o',
col = c("darkslategray1", "darkslategray3", "darkslategray4", "gray80", "coral", "wheat2"),
horiz=F)
dev.off()