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Chunk10-Validation of housekeeping genes.R
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Chunk10-Validation of housekeeping genes.R
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################################################################################
# &&&....&&& % Project: Identification of HKG candidates in C. elegans #
# &&&&&&..&&&&&& % Author: Bo Li, Jingxin Tao, Youjin Hao #
# &&&&&&&&&&&&&& % Date: Dec. 24th, 2019 #
# &&&&&&&&&&&& % #
# &&&&&&&& % Environment: R version 3.5.3; #
# &&&& % Platform: x86_64-pc-linux-gnu (64-bit) #
# & % #
################################################################################
###==========================================================================###
### ****************************************************************************
### code chunk number 09: Validation of housekeeping genes.
### ****************************************************************************
setwd("J:\\00-Paper Publication\\A2-HKG identification (Tao Jing-xin)\\Manuscript")
top50HKG <- get(load("Data/rank50_top5000_v2.RData"))
top100HKG <- get(load("Data/rank100_top5000_v2.RData"))
gpl200anno <- get(load("Data/gpl200anno.RData"))
for (n in 1:length(top100HKG)) {
probe.len <- length(top100HKG[[n]])
at.pos <- grep("_at", top100HKG[[n]])
at2sym <- NULL
for (g in at.pos) {
tp <- gpl200anno$`Gene Symbol`[match(top100HKG[[n]][g], gpl200anno$ID)]
print(g)
print(tp)
tmp <- strsplit(tp, " /// ")[[1]][1]
if (length(grep("WBGene", tmp)) != 0) {
x <- strsplit(tp, " /// ")[[1]][2]
tmp <- x
}
print(tmp)
at2sym <- c(at2sym, tmp)
}
top100HKG[[n]][at.pos] <- at2sym
}
names(top50HKG)[4] <- names(top100HKG)[4] <- "Li-Wong_exprs"
save(top50HKG, file = "rank50_top5000_v2.RData")
save(top100HKG, file = "rank100_top5000_v2.RData")
library(UpSetR)
# help(package = "UpSetR")
## ---------------- Venn plot for top 50 genes in six SGLs ------------------ ##
listInput <- list(RMA = top50HKG$RMA_exprs,
MAS5 = top50HKG$MAS_exprs,
gcRMA = top50HKG$GCRMA_exprs,
Li_Wong = top50HKG$`Li-Wong_exprs`,
PLIER = top50HKG$PLIER_exprs,
VSN = top50HKG$VSN_exprs)
df.listInput <- fromList(listInput)
col_seq <- c("#376092","#77933C","#993735","#604A7B","#31859C","#E46C0A" )
# #F08080 standing for the color named by LightCoral
hkgs50 <- upset(df.listInput,
sets = c ("RMA", "MAS5","gcRMA","Li_Wong", "PLIER","VSN"),
main.bar.color = "grey20",
queries = list(list(query = intersects,
params = list("PLIER", "Li_Wong", "MAS5", "RMA"),
color = "#F08080", active = TRUE),
list(query = intersects,
params = list("PLIER", "Li_Wong", "RMA"),
color = "#F08080", active = TRUE)
),
sets.bar.color = col_seq,
order.by = "degree")
hk4.top50 <- Reduce(intersect,
list(top50HKG$PLIER_exprs,
top50HKG$`Li-Wong_exprs`,
top50HKG$MAS_exprs,
top50HKG$RMA_exprs)
)
## ---------------- Venn plot for top 100 genes in six SGLs ----------------- ##
listInput <- list(RMA = top100HKG$RMA_exprs,
MAS5 = top100HKG$MAS_exprs,
gcRMA = top100HKG$GCRMA_exprs,
Li_Wong = top100HKG$`Li-Wong_exprs`,
PLIER = top100HKG$PLIER_exprs,
VSN = top100HKG$VSN_exprs)
df.listInput <- fromList(listInput)
col_seq <- c( "#376092","#77933C","#993735","#604A7B","#31859C","#E46C0A" )
upset(df.listInput,
sets = c ("RMA", "MAS5","gcRMA","Li_Wong", "PLIER","VSN"),
main.bar.color = "grey20",
queries = list(list(query = intersects,
params = list("PLIER", "Li_Wong", "MAS5", "RMA"),
color = "#F08080", active = TRUE),
list(query = intersects,
params = list("VSN", "Li_Wong", "RMA"),
color = "#F08080", active = TRUE),
list(query = intersects,
params = list("PLIER", "Li_Wong", "RMA"),
color = "#F08080", active = TRUE),
list(query = intersects,
params = list("PLIER", "MAS5", "RMA"),
color = "#F08080", active = TRUE), # coral red
list(query = intersects,
params = list("PLIER", "RMA"),
color = "violet", active = TRUE) # violet
),
sets.bar.color = col_seq,
order.by = "degree")
hk4.top100 <- Reduce(intersect,
list(top100HKG$PLIER_exprs,
top100HKG$`Li-Wong_exprs`,
top100HKG$MAS_exprs,
top100HKG$RMA_exprs)
)
hk3.1.top100 <- Reduce(intersect,
list(top100HKG$VSN_exprs,
top100HKG$`Li-Wong_exprs`,
top100HKG$RMA_exprs)
)
hk3.2.top100 <- Reduce(intersect,
list(top100HKG$PLIER_exprs,
top100HKG$`Li-Wong_exprs`,
top100HKG$RMA_exprs)
)
hk3.3.top100 <- Reduce(intersect,
list(top100HKG$PLIER_exprs,
top100HKG$MAS_exprs,
top100HKG$RMA_exprs)
)
hk2.top100 <- Reduce(intersect,
list(top100HKG$PLIER_exprs,
top100HKG$RMA_exprs)
)
hk2.top100 # rps-17
hk.3_4.100 <- unique(c(hk4.top100, hk3.1.top100, hk3.2.top100, hk3.3.top100))
# End of this line.