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Vallo Varik
32drugs
Commits
61de7b7b
Commit
61de7b7b
authored
May 31, 2022
by
Vallo Varik
Browse files
Added comments to Carlota's script
parent
9da48a30
Changes
1
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Task1.R
View file @
61de7b7b
library
(
ggplot2
)
library
(
dplyr
)
library
(
ggplot2
)
# VV: not needed, included in tidyverse
library
(
dplyr
)
# VV: not needed, included in tidiverse
library
(
tidyverse
)
# EXPLORE
## task1_1
data
<-
read.csv
(
"/Users/carlota/Desktop/EMBL/Vallo_R/01_dat.csv"
,
header
=
TRUE
)
# VV: A recommended practice is to keep your project/analysis in a single root
# folder and refer to files using relative path, something like this:
# data <- read.csv("01_dat.csv", header = TRUE) or better yet, organized into
# folders:
# data <- read.csv("input/data/01_dat.csv", header = TRUE)
# This way, you can copy the whole folder and run it on any computer.
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
)
# VV: just a reminder that you can use nrow & ncol argments with facet
# wrap. Here, it does not matter much, but sometimes controlling the
# alignement facilitates comparison.
facet_wrap
(
~
uM
,
labeller
=
label_both
)
ggsave
(
filename
=
"/Users/carlota/Desktop/EMBL/Vallo_R/plot1_1.pdf"
)
## task1_2
...
...
@@ -93,6 +102,7 @@ ggsave(filename = "/Users/carlota/Desktop/EMBL/Vallo_R/plot1_5.pdf")
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
)
...
...
@@ -100,7 +110,12 @@ data3 <- read.csv("/Users/carlota/Desktop/EMBL/Vallo_R/03_dat.csv", header = TRU
data3
$
OD
<-
ifelse
(
data3
$
OD
<
0.03
,
0.03
,
data3
$
OD
)
data3
<-
group_by
(
data3
,
Date
,
Time_h
,
Plt
)
%>%
# VV: You can, of course, call it any way you like, but fit_ref is a little
# misleading, OD_ref would be more to the point.
mutate
(
fit_ref
=
OD
[
uM
==
0
],
# VV: Here, at this step, you could right away use the `fit_ref` variable
# defined first in mutate call:
# fit = OD/fit_ref)
fit
=
OD
/
OD
[
uM
==
0
])
# constrain fitness to value of 1.1
...
...
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