-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathfig6.R
124 lines (107 loc) · 5.26 KB
/
fig6.R
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
library(ggplot2)
library(data.table)
std <- function(x) sd(x)/sqrt(length(x))
dtsize <- read.csv("/Users/mar/BIO/PROJECTS/APOBEC/NONBDNA/Denek3/united_X0.txt", sep='\t')
dtsize <- data.table(dtsize)
dtsize <- dtsize[APO == 0 & struID == "z",.(szIN,szOUall)]
dts <- unique(dtsize[,])
for(cancer in c("MELA-AU","SKCM-US")){
data <- read.csv(paste0("/Users/mar/BIO/PROJECTS/APOBEC/NONBDNA/ZDNA/Z_",cancer,".txt"),sep='\t')
data <- data.table(data)
dt <- unique(data[,.(tTCin,tTCout,tCTin,tCTout,tCCin,tCCout)])
dt2 <- cbind(dt,dts)
dt2[, tTCinRatio := tTCin / szIN]
dt2[, tTCoutRatio := tTCout / szOUall]
dt2[, tCTinRatio := tCTin / szIN]
dt2[, tCToutRatio := tCTout / szOUall]
dt2[, tCCinRatio := tCCin / szIN]
dt2[, tCCoutRatio := tCCout / szOUall]
dt2 <- dt2[,.(tTCinRatio,tTCoutRatio,tCCinRatio,tCCoutRatio)]
dt2melt <- melt(dt2)
dt2melt[,motif:=substr(variable,2,3)]
dt2melt[,region:=substr(variable,4,5)]
# update due to Gena's specific counting of targets
dt2melt[motif=='TC' & region == "in", value := 0.007927096]
dt2melt[motif=='TC' & region == "ou", value := 0.108816240]
ggplot(dt2melt,aes(x=motif,y=value,fill=region,color=region)) + geom_bar(stat="identity",position="dodge") +
theme(panel.background = element_blank(),
axis.title = element_blank(),
axis.line = element_line(color="black"),
axis.text.x = element_blank(),
legend.position = "none") +
scale_y_continuous(expand = c(0, 0), limits = c(0, NA)) +
scale_fill_manual(values = c(rgb(233,148,151,maxColorValue = 255),
rgb(146,187,216,maxColorValue = 255))) +
scale_color_manual(values = c(rgb(212,42,47,maxColorValue = 255),
rgb(38,120,178,maxColorValue = 255)))
ggsave(paste0("/Users/mar/BIO/PROJECTS/APOBEC/NONBDNA/pics/fig6/fig6b.tiff"),dpi=300,units="mm",width=70,height=50)
# dm <- data[,.(mTCin=sum(mTCin),
# mTCout=sum(mTCout),
# mCTin=sum(mCTin),
# mCTout=sum(mCTout),
# mcCin=sum(mcCin),
# mcCout=sum(mcCout),
# mCcin=sum(mCcin),
# mCcout=sum(mCcout))]
#
# dm2 <- cbind(dm,dt)
# dm2[, mTCinRatio := mTCin / tTCin]
# dm2[, mTCoutRatio := mTCout / tTCout]
# dm2[, mCTinRatio := mCTin / tCTin]
# dm2[, mCToutRatio := mCTout / tCTout]
# dm2[, mcCinRatio := mcCin / tCCin]
# dm2[, mcCoutRatio := mcCout / tCCout]
# dm2[, mCcinRatio := mCcin / tCCin]
# dm2[, mCcoutRatio := mCcout / tCCout]
data[, dTCin := mTCin / tTCin]
data[, dTCout := mTCout / tTCout]
data[, dCCin := (mcCin+mCcin) / tCCin]
data[, dCCout := (mcCout+mCcout) / tCCout ]
data[, dCTin := mCTin / tCTin]
data[, dCTout := mCTout / tCTout ]
data[, rTCin := dTCin/(dTCin+dTCout)]
data[, rTCout := dTCout/(dTCin+dTCout)]
data[, rCCin := dCCin/(dCCin+dCCout)]
data[, rCCout := dCCout/(dCCin+dCCout)]
data[, rCTin := dCTin/(dCTin+dCTout)]
data[, rCTout := dCTout/(dCTin+dCTout)]
dm <- data[(mcCin + mCcin) >= 5,.(rTCin,rTCout,rCCin,rCCout)]
print(wilcox.test(dm$rTCin,dm$rTCout))
print(wilcox.test(dm$rCCin,dm$rCCout))
dmMeans <- dm[,.("rTCin"=mean(rTCin),"rTCout"=mean(rTCout),"rCCin"=mean(rCCin),"rCCout"=mean(rCCout))]
dmSE <- dm[,.("rTCin"=std(rTCin),"rTCout"=std(rTCout),"rCCin"=std(rCCin),"rCCout"=std(rCCout))]
dmSTD <- dm[,.("rTCin"=sd(rTCin),"rTCout"=sd(rTCout),"rCCin"=sd(rCCin),"rCCout"=sd(rCCout))]
dm2 <- rbind(data.table("motif"="TC",
"region"="in",
"mean"=dmMeans$rTCin,
"sd"=dmSTD$rTCin,
"se"=dmSE$rTCin),
data.table("motif"="TC",
"region"="out",
"mean"=dmMeans$rTCout,
"sd"=dmSTD$rTCout,
"se"=dmSE$rTCout),
data.table("motif"="CC",
"region"="in",
"mean"=dmMeans$rCCin,
"sd"=dmSTD$rCCin,
"se"=dmSE$rCCin),
data.table("motif"="CC",
"region"="out",
"mean"=dmMeans$rCCout,
"sd"=dmSTD$rCCout,
"se"=dmSE$rCCout))
ggplot(dm2,aes(x=motif,y=mean,fill=region,color=region)) + geom_bar(stat="identity",position="dodge") +
geom_errorbar(aes(ymin=mean-sd, ymax=mean+sd),width=0.4, colour=rgb(38,120,178,maxColorValue = 255), alpha=0.9, size=0.5,position = position_dodge(0.9)) +
theme(panel.background = element_blank(),
axis.title = element_blank(),
axis.line = element_line(color="black"),
axis.text.x = element_blank(),
legend.position = "none") +
scale_y_continuous(expand = c(0, 0), limits = c(0, NA)) +
scale_fill_manual(values = c(rgb(233,148,151,maxColorValue = 255),
rgb(146,187,216,maxColorValue = 255))) +
scale_color_manual(values = c(rgb(212,42,47,maxColorValue = 255),
rgb(38,120,178,maxColorValue = 255)))
ggsave(paste0("/Users/mar/BIO/PROJECTS/APOBEC/NONBDNA/pics/fig6/fig6c_",cancer,".tiff"),dpi=300,units="mm",width=70,height=50)
}