-
Notifications
You must be signed in to change notification settings - Fork 3
/
wt_embryo_bar_graphs.R
165 lines (127 loc) · 8.09 KB
/
wt_embryo_bar_graphs.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
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
library(plyr)
library(readr)
library(ggplot2)
library("ggpubr", lib.loc="~/Library/R/3.6/library")
library(dplyr)
library(reshape2)
emf55 <- read.table("~/Dropbox (hannonlab)/Sequencing Data/roo/chipseq/emf55/new_sep20/individual/count/emf55_ind_count_roo_het_chr4.txt", header=T, fill = T, as.is = T)
emf55_roo <- as.data.frame(emf55[,2])
emf55_roo[,2] <-emf55[,4]*1000000/emf55[,3]
colnames(emf55_roo) <- c("timepoint", "value")
emf55_roo$timepoint <- factor(emf55_roo$timepoint,levels = unique(emf55_roo$timepoint))
ggboxplot(emf55_roo, x = "timepoint", y = "value", fill = "timepoint") +
ylab("Signal Intensity in RPM") +
xlab("time points") +
scale_y_continuous(breaks=c(c(10000,20000, 30000, 40000, 50000)), limits = c(0,50000)) +
scale_fill_brewer(palette="Set3") +
theme_classic() +
theme(axis.text.x = element_text(size = 15, angle = 90, hjust = .5, vjust = .5, face = "plain"),
axis.text.y = element_text(size = 15, angle = 0, hjust = .5, vjust = .5, face = "plain"),
axis.title.x = element_text(size = 15, angle = 0, hjust = .5, vjust = .5, face = "plain"),
axis.title.y = element_text(size = 15, angle = 90, hjust = .5, vjust = .5, face = "plain"))
ggsave(filename="~/Dropbox (hannonlab)/Sequencing Data/roo/chipseq/emf55/new_sep20/individual/count/emf55_boxplot_roo.pdf", plot = last_plot(), width=4, height=4)
emf55_het <- as.data.frame(emf55[,2])
emf55_het[,2] <-emf55[,5]*1000000/emf55[,3]
colnames(emf55_het) <- c("timepoint", "value")
emf55_het$timepoint <- factor(emf55_het$timepoint,levels = unique(emf55_het$timepoint))
ggboxplot(emf55_het, x = "timepoint", y = "value", fill = "timepoint") +
ylab("Signal Intensity in RPM") +
xlab("time points") +
scale_y_continuous(breaks=c(c(200000,400000,600000)), limits = c(0,600000)) +
scale_fill_brewer(palette="Set3") +
theme_classic() +
theme(axis.text.x = element_text(size = 15, angle = 90, hjust = .5, vjust = .5, face = "plain"),
axis.text.y = element_text(size = 15, angle = 0, hjust = .5, vjust = .5, face = "plain"),
axis.title.x = element_text(size = 15, angle = 0, hjust = .5, vjust = .5, face = "plain"),
axis.title.y = element_text(size = 15, angle = 90, hjust = .5, vjust = .5, face = "plain"))
ggsave(filename="~/Dropbox (hannonlab)/Sequencing Data/roo/chipseq/emf55/new_sep20/individual/count/emf55_boxplot_het.pdf", plot = last_plot(), width=4, height=4)
emf55_chr4 <- as.data.frame(emf55[,2])
emf55_chr4[,2] <-emf55[,6]*1000000/emf55[,3]
colnames(emf55_chr4) <- c("timepoint", "value")
emf55_chr4$timepoint <- factor(emf55_chr4$timepoint,levels = unique(emf55_chr4$timepoint))
ggboxplot(emf55_chr4, x = "timepoint", y = "value", fill = "timepoint") +
ylab("Signal Intensity in RPM") +
xlab("time points") +
scale_y_continuous(breaks=c(c(10000,20000,30000,40000,50000)), limits = c(0,50000)) +
scale_fill_brewer(palette="Set3") +
theme_classic() +
theme(axis.text.x = element_text(size = 15, angle = 90, hjust = .5, vjust = .5, face = "plain"),
axis.text.y = element_text(size = 15, angle = 0, hjust = .5, vjust = .5, face = "plain"),
axis.title.x = element_text(size = 15, angle = 0, hjust = .5, vjust = .5, face = "plain"),
axis.title.y = element_text(size = 15, angle = 90, hjust = .5, vjust = .5, face = "plain"))
ggsave(filename="~/Dropbox (hannonlab)/Sequencing Data/roo/chipseq/emf55/new_sep20/individual/count/emf55_boxplot_chr4.pdf", plot = last_plot(), width=4, height=4)
### Bar graphs
# roo
emf55_roo_reps <- emf55_roo %>% # the names of the new data frame and the data frame to be summarised
group_by(timepoint) %>% # the grouping variable
summarise(mean_PL = mean(value), # calculates the mean of each group
sd_PL = sd(value), # calculates the standard deviation of each group
n_PL = n(), # calculates the sample size per group
SE_PL = sd(value)/sqrt(n())) # calculates the standard error of each group
emf55_roo_reps$timepoint <- factor(emf55_roo_reps$timepoint, levels = unique(emf55_roo$timepoint))
emf55_roo_reps <- emf55_roo_reps[1:6,]
emf55_roo <- emf55_roo[1:12,]
ggplot(emf55_roo_reps, aes( y=mean_PL, x=timepoint)) +
geom_bar(position="dodge", stat="identity", fill = NA, colour = "red") +
geom_errorbar(aes(ymin = mean_PL - sd_PL, ymax = mean_PL + sd_PL), width=0.2) +
geom_point(data = emf55_roo, aes(y=value, x=timepoint),
stat="identity",
size=2,
shape=16,
position = position_dodge(width = .9)) +
geom_hline(yintercept=0) +
scale_y_continuous(expand = c(0,0),limits = c(0,45000)) +
scale_fill_manual(values = c("brown1", "skyblue2")) +
theme_classic() +
theme(axis.text.x = element_text(angle = 90, hjust = 1, colour="black"), axis.text.y = element_text( colour="black"), axis.ticks = element_line(colour="black"))
ggsave(filename="~/Desktop/figure3F_roo_bar_k9.pdf", plot = last_plot(), width=4, height=4)
#ggsave(filename="~/Dropbox (hannonlab)/Sequencing Data/roo/chipseq/emf55/new_sep20/individual/count/emf55_barplot_roo.pdf", plot = last_plot(), width=4, height=4)
# chr4
emf55_chr4_reps <- emf55_chr4 %>% # the names of the new data frame and the data frame to be summarised
group_by(timepoint) %>% # the grouping variable
summarise(mean_PL = mean(value), # calculates the mean of each group
sd_PL = sd(value), # calculates the standard deviation of each group
n_PL = n(), # calculates the sample size per group
SE_PL = sd(value)/sqrt(n())) # calculates the standard error of each group
emf55_chr4_reps$timepoint <- factor(emf55_chr4_reps$timepoint, levels = unique(emf55_roo$timepoint))
emf55_chr4_reps <- emf55_chr4_reps[1:6,]
emf55_chr4 <- emf55_chr4[1:12,]
ggplot(emf55_chr4_reps, aes( y=mean_PL, x=timepoint)) +
geom_bar(position="dodge", stat="identity", fill = NA, colour = "red") +
geom_errorbar(aes(ymin = mean_PL - sd_PL, ymax = mean_PL + sd_PL), width=0.2) +
geom_point(data = emf55_chr4, aes(y=value, x=timepoint),
stat="identity",
size=2,
shape=16,
position = position_dodge(width = .9)) +
geom_hline(yintercept=0) +
scale_y_continuous(expand = c(0,0),limits = c(0,50000)) +
scale_fill_manual(values = c("brown1", "skyblue2")) +
theme_classic() +
theme(axis.text.x = element_text(angle = 90, hjust = 1, colour="black"), axis.text.y = element_text( colour="black"), axis.ticks = element_line(colour="black"))
ggsave(filename="~/Desktop/figure3E_chr4_bar_k9.pdf", plot = last_plot(), width=4, height=4)
#ggsave(filename="~/Dropbox (hannonlab)/Sequencing Data/roo/chipseq/emf55/new_sep20/individual/count/emf55_barplot_chr4.pdf", plot = last_plot(), width=4, height=4)
# het
emf55_het_reps <- emf55_het %>% # the names of the new data frame and the data frame to be summarised
group_by(timepoint) %>% # the grouping variable
summarise(mean_PL = mean(value), # calculates the mean of each group
sd_PL = sd(value), # calculates the standard deviation of each group
n_PL = n(), # calculates the sample size per group
SE_PL = sd(value)/sqrt(n())) # calculates the standard error of each group
emf55_het_reps$timepoint <- factor(emf55_het_reps$timepoint, levels = unique(emf55_roo$timepoint))
emf55_het_reps <- emf55_het_reps[1:6,]
emf55_het <- emf55_het[1:12,]
ggplot(emf55_het_reps, aes( y=mean_PL, x=timepoint)) +
geom_bar(position="dodge", stat="identity", fill = NA, colour = "red") +
geom_errorbar(aes(ymin = mean_PL - sd_PL, ymax = mean_PL + sd_PL), width=0.2) +
geom_point(data = emf55_het, aes(y=value, x=timepoint),
stat="identity",
size=2,
shape=16,
position = position_dodge(width = .9)) +
geom_hline(yintercept=0) +
scale_y_continuous(expand = c(0,0),limits = c(0,400000)) +
scale_fill_manual(values = c("brown1", "skyblue2")) +
theme_classic() + theme(axis.text.x = element_text(angle = 90, hjust = 1))
ggsave(filename="~/Desktop/figure3D_het_bar_k9.pdf", plot = last_plot(), width=4, height=4)
#ggsave(filename="~/Dropbox (hannonlab)/Sequencing Data/roo/chipseq/emf55/new_sep20/individual/count/emf55_barplot_het.pdf", plot = last_plot(), width=4, height=4)