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Vallo Varik
32drugs
Commits
9da48a30
Commit
9da48a30
authored
May 21, 2022
by
Carlota Losa Mediavilla
Browse files
Last version Task-1
parent
3a0dee96
Changes
1
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Task1.R
0 → 100644
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9da48a30
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
(
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
,
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"
)
+
# transform to logarithmic scale using trans = "log2"
scale_y_continuous
(
trans
=
"log2"
)
+
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
,
Time_h
,
RawOD
,
uM
)
%>%
mutate
(
Date
=
as.factor
(
Date
))
%>%
# day 3 has to biological replicates so we need to group the data by Plate (Plt) using group = Plt
ggplot
(
aes
(
y
=
RawOD
,
x
=
Time_h
,
color
=
Date
,
group
=
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: substract background OD
data3
<-
read.csv
(
"/Users/carlota/Desktop/EMBL/Vallo_R/03_dat.csv"
,
header
=
TRUE
)
%>%
group_by
(
Date
,
Time_h
,
Plt
)
%>%
mutate
(
background
=
RawOD
[
uM
==
-1
],
OD
=
RawOD
-
background
)
# this creates two new variables: (1) background OD (OD for uM = -1 for each Date, Time and plate)
# (2 )the final OD, calculated by substracting the background from the RawOD readout
data3
%>%
select
(
Date
,
Plt
,
Time_h
,
OD
,
uM
)
%>%
mutate
(
Date
=
as.factor
(
Date
))
%>%
filter
(
!
str_detect
(
uM
,
"-1"
))
%>%
# drops background plot
ggplot
(
aes
(
y
=
OD
,
x
=
Time_h
,
color
=
Date
,
group
=
Plt
))
+
geom_line
()
+
labs
(
x
=
"Time (h)"
,
y
=
"OD"
)
+
scale_y_continuous
(
trans
=
"log2"
)
+
facet_wrap
(
~
uM
,
labeller
=
label_both
)
ggsave
(
filename
=
"/Users/carlota/Desktop/EMBL/Vallo_R/plot1_4.pdf"
)
# Another way of grouping the background OD for each date, plate and time
#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
#mutate(OD = RawOD - bg)
#task1_5: constrain OD to limit of detection (LOD)
data3
<-
read.csv
(
"/Users/carlota/Desktop/EMBL/Vallo_R/03_dat.csv"
,
header
=
TRUE
)
%>%
group_by
(
Date
,
Time_h
,
Plt
)
%>%
mutate
(
background
=
RawOD
[
uM
==
-1
],
OD
=
RawOD
-
background
)
# constrain OD variable to LOD of 0.03
data3
$
OD
<-
ifelse
(
data3
$
OD
<
0.03
,
0.03
,
data3
$
OD
)
data3
%>%
select
(
Date
,
Plt
,
Time_h
,
OD
,
uM
)
%>%
mutate
(
Date
=
as.factor
(
Date
))
%>%
filter
(
!
str_detect
(
uM
,
"-1"
))
%>%
# drops background plot
ggplot
(
aes
(
y
=
OD
,
x
=
Time_h
,
color
=
Date
,
group
=
Plt
))
+
geom_line
()
+
labs
(
x
=
"Time (h)"
,
y
=
"OD"
)
+
scale_y_continuous
(
trans
=
"log2"
)
+
facet_wrap
(
~
uM
,
labeller
=
label_both
)
ggsave
(
filename
=
"/Users/carlota/Desktop/EMBL/Vallo_R/plot1_5.pdf"
)
#task1_6: fitness
data3
<-
read.csv
(
"/Users/carlota/Desktop/EMBL/Vallo_R/03_dat.csv"
,
header
=
TRUE
)
%>%
group_by
(
Date
,
Time_h
,
Plt
)
%>%
mutate
(
background
=
RawOD
[
uM
==
-1
],
OD
=
RawOD
-
background
)
# constrain OD variable to LOD of 0.03
data3
$
OD
<-
ifelse
(
data3
$
OD
<
0.03
,
0.03
,
data3
$
OD
)
data3
<-
group_by
(
data3
,
Date
,
Time_h
,
Plt
)
%>%
mutate
(
fit_ref
=
OD
[
uM
==
0
],
fit
=
OD
/
OD
[
uM
==
0
])
# constrain fitness to value of 1.1
data3
$
fit
<-
ifelse
(
data3
$
fit
>
1.1
,
1.1
,
data3
$
fit
)
data3
%>%
select
(
Date
,
Time_h
,
Plt
,
OD
,
fit
,
uM
)
%>%
mutate
(
Date
=
as.factor
(
Date
))
%>%
filter
(
!
str_detect
(
uM
,
"-1"
))
%>%
# drops background plot
ggplot
(
aes
(
y
=
fit
,
x
=
Time_h
,
color
=
Date
,
group
=
Plt
))
+
geom_line
()
+
labs
(
x
=
"Time (h)"
,
y
=
"Fitness"
)
+
scale_y_continuous
(
breaks
=
c
(
0.3
,
0.6
,
0.9
,
1.2
),
limits
=
c
(
0.0
,
1.1
))
+
facet_wrap
(
~
uM
,
labeller
=
label_both
)
ggsave
(
filename
=
"/Users/carlota/Desktop/EMBL/Vallo_R/plot1_6.pdf"
)
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