Results
CHO IL1RN , sgRNA 2
#B2M Normalized
condition <- c("dCas9-VPR Only","sgRNA 2 Only","dCas9-VPR and sgRNA 2")
FD <- c(0.860054507,0.563504876, 2.006943497)
SD <- c(0.019286252, 0.009587311, 0.017615696)
a <- data.frame(condition, FD, SD)
head(a)
## condition FD SD
## 1 dCas9-VPR Only 0.8600545 0.019286252
## 2 sgRNA 2 Only 0.5635049 0.009587311
## 3 dCas9-VPR and sgRNA 2 2.0069435 0.017615696
a %>% ggplot(aes(x= condition, y = FD)) +
geom_bar(stat="identity") +
geom_errorbar(aes(ymin=FD-SD, ymax=FD+SD), width=.2)+
xlab("Condition") +
ylab("Fold Difference over Transfected Dark") +
theme_economist() +
ggtitle("CHO IL1RN sgRNA 2") +
labs(subtitle="B2M Normalized") +
ggsave(filename = "CHO_IL1RN_sgRNA_2", device = "png", # saving the map
plot = last_plot(), # you have to run the plotting code above right before this code so it's saves the correct last plot plotted
width = 5, height = 5, units = "in", # dimensions
dpi = 300)
CHO IL1RN , sgRNA 3
#B2M Normalized
condition <- c("dCas9-VPR Only","sgRNA 3 Only","dCas9-VPR and sgRNA 3")
FD <- c(0.860054507, 0.533108097, 0.784584098)
SD <- c(0.019286252,0.010719622,0.028933304)
b <- data.frame(condition, FD, SD)
head(b)
## condition FD SD
## 1 dCas9-VPR Only 0.8600545 0.01928625
## 2 sgRNA 3 Only 0.5331081 0.01071962
## 3 dCas9-VPR and sgRNA 3 0.7845841 0.02893330
b %>% ggplot(aes(x= condition, y = FD)) +
geom_bar(stat="identity") +
geom_errorbar(aes(ymin=FD-SD, ymax=FD+SD), width=.2)+
xlab("Condition") +
ylab("Fold Difference over Transfected Dark") +
theme_economist() +
ggtitle("CHO IL1RN , sgRNA 3") +
labs(subtitle="B2M Normalized") +
ggsave(filename = "CHO_IL1RN_sgRNA_3", device = "png", # saving the map
plot = last_plot(), # you have to run the plotting code above right before this code so it's saves the correct last plot plotted
width = 5, height = 5, units = "in", # dimensions
dpi = 300)
MM IL1RN sgRNA2
#GADPH Normalized
condition <- c("dCas9-VPR Only","sgRNA 2 Only","dCas9-VPR and sgRNA 2")
FD <- c(3.958626626,8.441503632,8.210670271)
SD <- c(0.107609013,0.254504684,0.242298516)
c <- data.frame(condition, FD, SD)
head(c)
## condition FD SD
## 1 dCas9-VPR Only 3.958627 0.1076090
## 2 sgRNA 2 Only 8.441504 0.2545047
## 3 dCas9-VPR and sgRNA 2 8.210670 0.2422985
c %>% ggplot(aes(x= condition, y = FD)) +
geom_bar(stat="identity") +
geom_errorbar(aes(ymin=FD-SD, ymax=FD+SD), width=.2)+
xlab("Condition") +
ylab("Fold Difference over Transfected Dark") +
theme_economist() +
ggtitle("MM IL1RN sgRNA2") +
labs(subtitle="GADPH Normalized") +
ggsave(filename = "MM_IL1RN_sgRNA2", device = "png", # saving the map
plot = last_plot(), # you have to run the plotting code above right before this code so it's saves the correct last plot plotted
width = 5, height = 5, units = "in", # dimensions
dpi = 300)
MM IL1RN sgRNA3
#GADPH Normalized
condition <- c("dCas9-VPR Only","sgRNA 3 Only","dCas9-VPR and sgRNA 3")
FD <- c(3.958626626,3.005281225,6.408559021)
SD <- c(0.107609013,0.08078474,0.19284373)
d <- data.frame(condition, FD, SD)
head(d)
## condition FD SD
## 1 dCas9-VPR Only 3.958627 0.10760901
## 2 sgRNA 3 Only 3.005281 0.08078474
## 3 dCas9-VPR and sgRNA 3 6.408559 0.19284373
d %>% ggplot(aes(x= condition, y = FD)) +
geom_bar(stat="identity") +
geom_errorbar(aes(ymin=FD-SD, ymax=FD+SD), width=.2)+
xlab("Condition") +
ylab("Fold Difference over Transfected Dark") +
theme_economist() +
ggtitle("MM IL1RN sgRNA3") +
labs(subtitle="GADPH Normalized") +
ggsave(filename = "MM_IL1RN_sgRNA3", device = "png", # saving the map
plot = last_plot(), # you have to run the plotting code above right before this code so it's saves the correct last plot plotted
width = 5, height = 5, units = "in", # dimensions
dpi = 300)
MM CXCR4 sgRNA2
#GADPH Normalized
condition <- c("dCas9-VPR Only","sgRNA 2 Only","dCas9-VPR and sgRNA 2")
FD <- c(3.958626626,19.29292524,23.26356028)
SD <- c(0.107609013,0.247284735,0.439233703)
e <- data.frame(condition, FD, SD)
head(e)
## condition FD SD
## 1 dCas9-VPR Only 3.958627 0.1076090
## 2 sgRNA 2 Only 19.292925 0.2472847
## 3 dCas9-VPR and sgRNA 2 23.263560 0.4392337
e %>% ggplot(aes(x= condition, y = FD)) +
geom_bar(stat="identity") +
geom_errorbar(aes(ymin=FD-SD, ymax=FD+SD), width=.2)+
xlab("Condition") +
ylab("Fold Difference over Transfected Dark") +
theme_economist() +
ggtitle("MM CXCR4 sgRNA2") +
labs(subtitle="GADPH Normalized") +
ggsave(filename = "MM_CXCR4_sgRNA2", device = "png", # saving the map
plot = last_plot(), # you have to run the plotting code above right before this code so it's saves the correct last plot plotted
width = 5, height = 5, units = "in", # dimensions
dpi = 300)
MM CXCR4 sgRNA3
#GADPH Normalized
condition <- c("dCas9-VPR Only","sgRNA 3 Only","dCas9-VPR and sgRNA 3")
FD <- c(3.958626626,7.14780363,10.64792198)
SD <- c(0.107609013,0.107062544,0.409815562)
f <- data.frame(condition, FD, SD)
head(f)
## condition FD SD
## 1 dCas9-VPR Only 3.958627 0.1076090
## 2 sgRNA 3 Only 7.147804 0.1070625
## 3 dCas9-VPR and sgRNA 3 10.647922 0.4098156
f %>% ggplot(aes(x= condition, y = FD)) +
geom_bar(stat="identity") +
geom_errorbar(aes(ymin=FD-SD, ymax=FD+SD), width=.2)+
xlab("Condition") +
ylab("Fold Difference over Transfected Dark") +
theme_economist() +
ggtitle("MM CXCR4 sgRNA3") +
labs(subtitle="GADPH Normalized") +
ggsave(filename = "MM_CXCR4_sgRNA3", device = "png", # saving the map
plot = last_plot(), # you have to run the plotting code above right before this code so it's saves the correct last plot plotted
width = 5, height = 5, units = "in", # dimensions
dpi = 300)
CHO IL1RN Combination sgRNA
#B2M Normalized
condition <- c("dCas9-VPR Only", "sgRNA 2 Only", "sgRNA 3 Only", "sgRNA 2, 3", "dCas9-VPR, sgRNA 2", "dCas9-VPR, sgRNA 3", "dCas9-VPR, sgRNA 2, sgRNA 3")
FD <- c(1.0811,0.533108,0.563505,2.652771,0.784584,2.006943,2.134281)
SD <- c(0.026519,0.008665,0.009803,0.025907,0.016548,0.024464,0.245629)
g <- data.frame(condition, FD, SD)
head(g)
## condition FD SD
## 1 dCas9-VPR Only 1.081100 0.026519
## 2 sgRNA 2 Only 0.533108 0.008665
## 3 sgRNA 3 Only 0.563505 0.009803
## 4 sgRNA 2, 3 2.652771 0.025907
## 5 dCas9-VPR, sgRNA 2 0.784584 0.016548
## 6 dCas9-VPR, sgRNA 3 2.006943 0.024464
g %>% ggplot(aes(x= condition, y = FD)) +
geom_bar(stat="identity") +
geom_errorbar(aes(ymin=FD-SD, ymax=FD+SD), width=.2)+
xlab("Condition") +
ylab("Fold Difference over Transfected Dark") +
theme_economist() +
theme(text = element_text(size=5)) +
ggtitle("CHO IL1RN Combination sgRNA") +
labs(subtitle="B2M Normalized") +
ggsave(filename = "CHO_IL1RN_Combination_sgRNA", device = "png", # saving the map
plot = last_plot(), # you have to run the plotting code above right before this code so it's saves the correct last plot plotted
width = 8, height = 5, units = "in", # dimensions
dpi = 300)
NIH 3T3 sgRNA Composite
#GAPDH Normalized
condition <- c("dCas9-VPR Only","sgRNA 2 Only","sgRNA 3 Only","sgRNA 2 and 3","dCas9-VPR and sgRNA 2","dCas9-VPR and sgRNA 3","dCas9-VPR, sgRNA 2, sgRNA 3")
FD <- c(4.240301,8.441504,3.005281,8.069616,8.21067,6.408559,6.526231)
SD <- c(0.126713,0.254505,0.080785,0.307053,0.242299,0.192844,1.035593)
h <- data.frame(condition, FD, SD)
head(h)
## condition FD SD
## 1 dCas9-VPR Only 4.240301 0.126713
## 2 sgRNA 2 Only 8.441504 0.254505
## 3 sgRNA 3 Only 3.005281 0.080785
## 4 sgRNA 2 and 3 8.069616 0.307053
## 5 dCas9-VPR and sgRNA 2 8.210670 0.242299
## 6 dCas9-VPR and sgRNA 3 6.408559 0.192844
h %>% ggplot(aes(x= condition, y = FD)) +
geom_bar(stat="identity") +
geom_errorbar(aes(ymin=FD-SD, ymax=FD+SD), width=.2)+
xlab("Condition") +
ylab("Fold Difference over Transfected Dark") +
theme_economist() +
theme(text = element_text(size=5)) +
labs(subtitle="GADPH Normalized") +
ggtitle("NIH 3T3 sgRNA Composite sgRNA") +
ggsave(filename = "NIH_3T3_sgRNA_Composite_sgRNA", device = "png", # saving the map
plot = last_plot(), # you have to run the plotting code above right before this code so it's saves the correct last plot plotted
width = 8, height = 5, units = "in", # dimensions
dpi = 300)
NEU Comparison
#RN18S Normalized
condition <- c("VP64 Activator","VPR Activator","NEU VP64 Activator")
FD <- c(2.175982,0.955945,0.768438)
SD <- c(0.087505,0.031331,0.028046)
i <- data.frame(condition, FD, SD)
head(h)
## condition FD SD
## 1 dCas9-VPR Only 4.240301 0.126713
## 2 sgRNA 2 Only 8.441504 0.254505
## 3 sgRNA 3 Only 3.005281 0.080785
## 4 sgRNA 2 and 3 8.069616 0.307053
## 5 dCas9-VPR and sgRNA 2 8.210670 0.242299
## 6 dCas9-VPR and sgRNA 3 6.408559 0.192844
i %>% ggplot(aes(x= condition, y = FD)) +
geom_bar(stat="identity") +
geom_errorbar(aes(ymin=FD-SD, ymax=FD+SD), width=.2)+
xlab("Condition") +
ylab("Fold Difference over Transfected Dark") +
theme_economist() +
#theme(text = element_text(size=)) +
labs(subtitle="GADPH Normalized") +
ggtitle("NEU CRY2 Comparison") +
ggsave(filename = "NEU_comparison", device = "png", # saving the map
plot = last_plot(), # you have to run the plotting code above right before this code so it's saves the correct last plot plotted
width = 8, height = 5, units = "in", # dimensions
dpi = 300)
