Task1

Task1.R

+library(ggplot2)
+library(dplyr)
+library(tidyverse)
+
+# EXPLORE
+## task1_1
+data <- read.csv("/Users/carlota/Desktop/EMBL/Vallo_R/01_dat.csv", header = TRUE) 
+data %>% 
+        select(Well, Time_h, RawOD, uM) %>%
+        ggplot(aes(y= RawOD, x = Time_h)) +
+        geom_line() +
+        labs(x = "Time (h)", y = "Raw OD", title = "Growth curves of S.flexneri M90T with Azithromycin") +
+        facet_wrap(~ uM, labeller = label_both)
+ggsave(filename = "/Users/carlota/Desktop/EMBL/Vallo_R/plot1_1.pdf")
+
+## task1_2
+data2 <- read.csv("/Users/carlota/Desktop/EMBL/Vallo_R/02_dat.csv", header = TRUE)
+data2 %>%
+        select(Date, Well, Time_h, RawOD, uM) %>%
+        mutate(Date = as.factor(Date)) %>%
+        ggplot(aes(y= RawOD, x = Time_h, color = Date)) +
+        geom_line() + 
+        labs(x = "Time (h)", y = "RawOD") +
+        scale_y_continuous(trans = "log2") + # transforms to logarithmic scale
+        facet_wrap(~ uM, labeller = label_both)
+ggsave(filename = "/Users/carlota/Desktop/EMBL/Vallo_R/plot1_2.pdf")
+
+## task1_3
+data3 <- read.csv("/Users/carlota/Desktop/EMBL/Vallo_R/03_dat.csv", header = TRUE)
+data3 %>%
+        select(Date, Plt, Well, Time_h, RawOD, uM) %>%
+        mutate(Date = as.factor(Date)) %>%
+        ggplot(aes(y= RawOD, x = Time_h, color = Date, group = Plt)) + # groups according to Plt
+        geom_line() + 
+        labs(x = "Time (h)", y = "RawOD") +
+        scale_y_continuous(trans = "log2") +
+        facet_wrap(~ uM, labeller = label_both)
+ggsave(filename = "/Users/carlota/Desktop/EMBL/Vallo_R/plot1_3.pdf")
+
+
+# TRANSFORM
+
+## task1_4
+data3 <- read.csv("/Users/carlota/Desktop/EMBL/Vallo_R/03_dat.csv", header = TRUE) %>% 
+        group_by(Date, Time_h, Plt) %>% 
+        #now assign new variables
+        mutate(  
+                background = RawOD[uM ==-1],
+                OD = RawOD - background)  
+        #filter(Time_h == 1.08) 
+
+#data3$OD <- data3$RawOD - filter(data3, uM == -1)$RawOD
+data3 %>%
+        select(Date, Plt, Well, Time_h, OD, RawOD, uM) %>%
+        mutate(Date = as.factor(Date)) %>% # is it RawOD or OD?
+        filter(!str_detect(uM, "-1")) %>%
+        ggplot(aes(y= OD, x = Time_h, color = Date, group = Plt)) + # groups according to Plt
+        geom_line() + 
+        labs(x = "Time (h)", y = "RawOD") +
+        scale_y_continuous(trans = "log2") +
+        facet_wrap(~ uM, labeller = label_both)
+ggsave(filename = "/Users/carlota/Desktop/EMBL/Vallo_R/plot1_4.pdf")
+
+data3 <- filter(data3, uM == -1) %>%
+        rename(bg= RawOD) %>% 
+        select(Date, Plt, Time_h, bg) %>% 
+        right_join(data3) # it matches back based on date, plt and time_h
+
+        
+        
+
+