Supplementary_Data_35
Denis
2023-07-10
RT-qPCR analysis - FGF9 - outlier identification by the IQR method in R
rm(list=ls())library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.4.4 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.0
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors1 FGF9
1.1 FGF9_iPS09
1.1.1 FGF9_iPS09-M1_36h00-Wt
Input = ("
names values block
WT 12.46 iPS09-45-M1_36h00
WT 12.55 iPS09-45-M1_36h00
WT 11.82 iPS09-45-M1_36h00
WT 13.03 iPS09-45-M1_36h00
WT 11.69 iPS09-45-M1_36h00
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data4 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data4)
Data4b<- Data4|> select(block, names, values, values_wo_outliers)
Data4b## block names values values_wo_outliers
## 1 iPS09-45-M1_36h00 WT 12.46 12.46
## 2 iPS09-45-M1_36h00 WT 12.55 12.55
## 3 iPS09-45-M1_36h00 WT 11.82 11.82
## 4 iPS09-45-M1_36h00 WT 13.03 13.03
## 5 iPS09-45-M1_36h00 WT 11.69 11.691.1.2 FGF9_iPS09-M1_36h00-Mut
Input = ("
names values block
Mut 11.17 iPS09-82-M1_36h00
Mut 11.65 iPS09-82-M1_36h00
Mut 12.31 iPS09-82-M1_36h00
Mut 11.03 iPS09-82-M1_36h00
Mut 10.36 iPS09-82-M1_36h00
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data5 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data5)
Data5b<- Data5|> select(block, names, values, values_wo_outliers)
Data5b## block names values values_wo_outliers
## 1 iPS09-82-M1_36h00 Mut 11.17 11.17
## 2 iPS09-82-M1_36h00 Mut 11.65 11.65
## 3 iPS09-82-M1_36h00 Mut 12.31 12.31
## 4 iPS09-82-M1_36h00 Mut 11.03 11.03
## 5 iPS09-82-M1_36h00 Mut 10.36 10.361.1.3 FGF9_iPS09-M2_24h00-Wt
Input = ("
names values block
WT 12.99 iPS09-45-M2_24h00
WT 12.28 iPS09-45-M2_24h00
WT 13.07 iPS09-45-M2_24h00
WT 12.03 iPS09-45-M2_24h00
WT 12.28 iPS09-45-M2_24h00
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data6 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data6)
Data6b<- Data6|> select(block, names, values, values_wo_outliers)
Data6b## block names values values_wo_outliers
## 1 iPS09-45-M2_24h00 WT 12.99 12.99
## 2 iPS09-45-M2_24h00 WT 12.28 12.28
## 3 iPS09-45-M2_24h00 WT 13.07 13.07
## 4 iPS09-45-M2_24h00 WT 12.03 12.03
## 5 iPS09-45-M2_24h00 WT 12.28 12.281.1.4 FGF9_iPS09-M2_24h00-Mut
Input = ("
names values block
Mut 10.18 iPS09-82-M2_24h00
Mut 11.28 iPS09-82-M2_24h00
Mut 10.56 iPS09-82-M2_24h00
Mut 10.53 iPS09-82-M2_24h00
Mut 11.17 iPS09-82-M2_24h00
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data7 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data7)
Data7b<- Data7|> select(block, names, values, values_wo_outliers)
Data7b## block names values values_wo_outliers
## 1 iPS09-82-M2_24h00 Mut 10.18 10.18
## 2 iPS09-82-M2_24h00 Mut 11.28 11.28
## 3 iPS09-82-M2_24h00 Mut 10.56 10.56
## 4 iPS09-82-M2_24h00 Mut 10.53 10.53
## 5 iPS09-82-M2_24h00 Mut 11.17 11.171.1.5 FGF9_iPS09-M3_24h00-Wt
Input = ("
names values block
WT 12.84 iPS09-45-M3_24h00
WT 12.27 iPS09-45-M3_24h00
WT 12.63 iPS09-45-M3_24h00
WT 11.92 iPS09-45-M3_24h00
WT 12.37 iPS09-45-M3_24h00
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data8 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data8)
Data8b<- Data8|> select(block, names, values, values_wo_outliers)
Data8b## block names values values_wo_outliers
## 1 iPS09-45-M3_24h00 WT 12.84 12.84
## 2 iPS09-45-M3_24h00 WT 12.27 12.27
## 3 iPS09-45-M3_24h00 WT 12.63 12.63
## 4 iPS09-45-M3_24h00 WT 11.92 11.92
## 5 iPS09-45-M3_24h00 WT 12.37 12.371.1.6 FGF9_iPS09-M3_48h00-Wt
Input = ("
names values block
WT 13.75 iPS09-45-M3_48h00
WT 12.87 iPS09-45-M3_48h00
WT 13.21 iPS09-45-M3_48h00
WT 13.60 iPS09-45-M3_48h00
WT 12.22 iPS09-45-M3_48h00
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data9 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data9)
Data9b<- Data9|> select(block, names, values, values_wo_outliers)
Data9b## block names values values_wo_outliers
## 1 iPS09-45-M3_48h00 WT 13.75 13.75
## 2 iPS09-45-M3_48h00 WT 12.87 12.87
## 3 iPS09-45-M3_48h00 WT 13.21 13.21
## 4 iPS09-45-M3_48h00 WT 13.60 13.60
## 5 iPS09-45-M3_48h00 WT 12.22 12.221.1.7 FGF9_iPS09-M3_48h00-Mut
Input = ("
names values block
Mut 13.14 iPS09-82-M3_48h00
Mut 12.01 iPS09-82-M3_48h00
Mut 11.46 iPS09-82-M3_48h00
Mut 12.17 iPS09-82-M3_48h00
Mut 12.36 iPS09-82-M3_48h00
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data10 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data10)
Data10b<- Data10|> select(block, names, values, values_wo_outliers)
Data10b## block names values values_wo_outliers
## 1 iPS09-82-M3_48h00 Mut 13.14 NA
## 2 iPS09-82-M3_48h00 Mut 12.01 12.01
## 3 iPS09-82-M3_48h00 Mut 11.46 NA
## 4 iPS09-82-M3_48h00 Mut 12.17 12.17
## 5 iPS09-82-M3_48h00 Mut 12.36 12.361.2 FGF9_iPS12
1.2.1 FGF9_iPS12-M1_36h00-Wt
Input = ("
names values block
WT 12.88 iPS12_45_M1_36_P
WT 12.50 iPS12_45_M1_36_P
WT 12.58 iPS12_45_M1_36_P
WT 12.51 iPS12_45_M1_36_P
WT 12.85 iPS12_45_M1_36_P
WT 12.37 iPS12_45_M1_36_P
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data13 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data13)
Data13b<- Data13|> select(block, names, values, values_wo_outliers)
Data13b## block names values values_wo_outliers
## 1 iPS12_45_M1_36_P WT 12.88 12.88
## 2 iPS12_45_M1_36_P WT 12.50 12.50
## 3 iPS12_45_M1_36_P WT 12.58 12.58
## 4 iPS12_45_M1_36_P WT 12.51 12.51
## 5 iPS12_45_M1_36_P WT 12.85 12.85
## 6 iPS12_45_M1_36_P WT 12.37 12.371.2.2 FGF9_iPS12-M1_36h00-Mut
Input = ("
names values block
Mut 11.38 iPS12_82_M1_36_P
Mut 11.41 iPS12_82_M1_36_P
Mut 12.00 iPS12_82_M1_36_P
Mut 11.42 iPS12_82_M1_36_P
Mut 11.25 iPS12_82_M1_36_P
Mut 11.36 iPS12_82_M1_36_P
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data14 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data14)
Data14b<- Data14|> select(block, names, values, values_wo_outliers)
Data14b## block names values values_wo_outliers
## 1 iPS12_82_M1_36_P Mut 11.38 11.38
## 2 iPS12_82_M1_36_P Mut 11.41 11.41
## 3 iPS12_82_M1_36_P Mut 12.00 NA
## 4 iPS12_82_M1_36_P Mut 11.42 11.42
## 5 iPS12_82_M1_36_P Mut 11.25 NA
## 6 iPS12_82_M1_36_P Mut 11.36 11.361.2.3 FGF9_iPS12-M2_06h00-Wt
Input = ("
names values block
WT 13.56 iPS12_45_M2_06_P
WT 13.50 iPS12_45_M2_06_P
WT 13.07 iPS12_45_M2_06_P
WT 13.56 iPS12_45_M2_06_P
WT 13.38 iPS12_45_M2_06_P
WT NA iPS12_45_M2_06_P
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data15 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data15)
Data15b<- Data15|> select(block, names, values, values_wo_outliers)
Data15b## block names values values_wo_outliers
## 1 iPS12_45_M2_06_P WT 13.56 13.56
## 2 iPS12_45_M2_06_P WT 13.50 13.50
## 3 iPS12_45_M2_06_P WT 13.07 NA
## 4 iPS12_45_M2_06_P WT 13.56 13.56
## 5 iPS12_45_M2_06_P WT 13.38 13.38
## 6 iPS12_45_M2_06_P WT NA NA1.2.4 FGF9_iPS12-M2_06h00-Mut
Input = ("
names values block
Mut 11.97 iPS12_82_M2_06_P
Mut 11.82 iPS12_82_M2_06_P
Mut 11.85 iPS12_82_M2_06_P
Mut 11.93 iPS12_82_M2_06_P
Mut 12.27 iPS12_82_M2_06_P
Mut 12.24 iPS12_82_M2_06_P
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data16 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data16)
Data16b<- Data16|> select(block, names, values, values_wo_outliers)
Data16b## block names values values_wo_outliers
## 1 iPS12_82_M2_06_P Mut 11.97 11.97
## 2 iPS12_82_M2_06_P Mut 11.82 11.82
## 3 iPS12_82_M2_06_P Mut 11.85 11.85
## 4 iPS12_82_M2_06_P Mut 11.93 11.93
## 5 iPS12_82_M2_06_P Mut 12.27 12.27
## 6 iPS12_82_M2_06_P Mut 12.24 12.241.2.5 FGF9_iPS12-M2_12h00-Wt
Input = ("
names values block
WT 13.69 iPS12_45_M2_12_P
WT 12.88 iPS12_45_M2_12_P
WT 12.89 iPS12_45_M2_12_P
WT 13.41 iPS12_45_M2_12_P
WT 12.92 iPS12_45_M2_12_P
WT 13.12 iPS12_45_M2_12_P
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data17 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data17)
Data17b<- Data17|> select(block, names, values, values_wo_outliers)
Data17b## block names values values_wo_outliers
## 1 iPS12_45_M2_12_P WT 13.69 13.69
## 2 iPS12_45_M2_12_P WT 12.88 12.88
## 3 iPS12_45_M2_12_P WT 12.89 12.89
## 4 iPS12_45_M2_12_P WT 13.41 13.41
## 5 iPS12_45_M2_12_P WT 12.92 12.92
## 6 iPS12_45_M2_12_P WT 13.12 13.121.2.6 FGF9_iPS12-M2_12h00-Mut
Input = ("
names values block
Mut 11.23 iPS12_82_M2_12_P
Mut 11.14 iPS12_82_M2_12_P
Mut 11.79 iPS12_82_M2_12_P
Mut 11.10 iPS12_82_M2_12_P
Mut 11.55 iPS12_82_M2_12_P
Mut 11.26 iPS12_82_M2_12_P
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data18 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data18)
Data18b<- Data18|> select(block, names, values, values_wo_outliers)
Data18b## block names values values_wo_outliers
## 1 iPS12_82_M2_12_P Mut 11.23 11.23
## 2 iPS12_82_M2_12_P Mut 11.14 11.14
## 3 iPS12_82_M2_12_P Mut 11.79 11.79
## 4 iPS12_82_M2_12_P Mut 11.10 11.10
## 5 iPS12_82_M2_12_P Mut 11.55 11.55
## 6 iPS12_82_M2_12_P Mut 11.26 11.261.2.7 FGF9_iPS12_M2_24h00-Wt
Input = ("
names values block
WT 13.20 iPS12_45_M2_24_P
WT 13.68 iPS12_45_M2_24_P
WT 13.14 iPS12_45_M2_24_P
WT 13.34 iPS12_45_M2_24_P
WT 13.22 iPS12_45_M2_24_P
WT 14.48 iPS12_45_M2_24_P
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data19 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data19)
Data19b<- Data19|> select(block, names, values, values_wo_outliers)
Data19b## block names values values_wo_outliers
## 1 iPS12_45_M2_24_P WT 13.20 13.20
## 2 iPS12_45_M2_24_P WT 13.68 13.68
## 3 iPS12_45_M2_24_P WT 13.14 13.14
## 4 iPS12_45_M2_24_P WT 13.34 13.34
## 5 iPS12_45_M2_24_P WT 13.22 13.22
## 6 iPS12_45_M2_24_P WT 14.48 NA1.2.8 FGF9_iPS12_M2_24h00-Mut
Input = ("
names values block
Mut 12.18 iPS12_82_M2_24_P
Mut 11.90 iPS12_82_M2_24_P
Mut 12.24 iPS12_82_M2_24_P
Mut 11.95 iPS12_82_M2_24_P
Mut 11.85 iPS12_82_M2_24_P
Mut 12.25 iPS12_82_M2_24_P
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data20 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data20)
Data20b<- Data20|> select(block, names, values, values_wo_outliers)
Data20b## block names values values_wo_outliers
## 1 iPS12_82_M2_24_P Mut 12.18 12.18
## 2 iPS12_82_M2_24_P Mut 11.90 11.90
## 3 iPS12_82_M2_24_P Mut 12.24 12.24
## 4 iPS12_82_M2_24_P Mut 11.95 11.95
## 5 iPS12_82_M2_24_P Mut 11.85 11.85
## 6 iPS12_82_M2_24_P Mut 12.25 12.251.2.9 FGF9_iPS12-M2_48h00-Wt
Input = ("
names values block
WT 12.55 iPS12_45_M2_48_P
WT 13.25 iPS12_45_M2_48_P
WT 12.86 iPS12_45_M2_48_P
WT 12.59 iPS12_45_M2_48_P
WT 13.29 iPS12_45_M2_48_P
WT NA iPS12_45_M2_48_P
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data21 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data21)
Data21b<- Data21|> select(block, names, values, values_wo_outliers)
Data21b## block names values values_wo_outliers
## 1 iPS12_45_M2_48_P WT 12.55 12.55
## 2 iPS12_45_M2_48_P WT 13.25 13.25
## 3 iPS12_45_M2_48_P WT 12.86 12.86
## 4 iPS12_45_M2_48_P WT 12.59 12.59
## 5 iPS12_45_M2_48_P WT 13.29 13.29
## 6 iPS12_45_M2_48_P WT NA NA1.2.10 FGF9_iPS12-M2_48h00-Mut
Input = ("
names values block
Mut 11.57 iPS12_82_M2_48_P
Mut 11.96 iPS12_82_M2_48_P
Mut 12.34 iPS12_82_M2_48_P
Mut 11.64 iPS12_82_M2_48_P
Mut 12.02 iPS12_82_M2_48_P
Mut 12.01 iPS12_82_M2_48_P
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# FGF9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data22 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data22)
Data22b<- Data22|> select(block, names, values, values_wo_outliers)
Data22b## block names values values_wo_outliers
## 1 iPS12_82_M2_48_P Mut 11.57 11.57
## 2 iPS12_82_M2_48_P Mut 11.96 11.96
## 3 iPS12_82_M2_48_P Mut 12.34 12.34
## 4 iPS12_82_M2_48_P Mut 11.64 11.64
## 5 iPS12_82_M2_48_P Mut 12.02 12.02
## 6 iPS12_82_M2_48_P Mut 12.01 12.011.3 FGF9_iPS19
1.3.1 FGF9_iPS19-iPS-Wt
Input = ("
names values block
WT 14.63 iPS19_45_iPS
WT 14.54 iPS19_45_iPS
WT 14.30 iPS19_45_iPS
WT 14.83 iPS19_45_iPS
WT 14.59 iPS19_45_iPS
WT 14.32 iPS19_45_iPS
WT 13.97 iPS19_82_iPS
WT 14.13 iPS19_82_iPS
WT 13.91 iPS19_82_iPS
WT 14.54 iPS19_82_iPS
WT 14.19 iPS19_82_iPS
WT 13.80 iPS19_82_iPS
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# SRY_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data23 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data23)
Data23b<- Data23|> select(block, names, values, values_wo_outliers)
Data23b## block names values values_wo_outliers
## 1 iPS19_45_iPS WT 14.63 14.63
## 2 iPS19_45_iPS WT 14.54 14.54
## 3 iPS19_45_iPS WT 14.30 14.30
## 4 iPS19_45_iPS WT 14.83 14.83
## 5 iPS19_45_iPS WT 14.59 14.59
## 6 iPS19_45_iPS WT 14.32 14.32
## 7 iPS19_82_iPS WT 13.97 13.97
## 8 iPS19_82_iPS WT 14.13 14.13
## 9 iPS19_82_iPS WT 13.91 13.91
## 10 iPS19_82_iPS WT 14.54 14.54
## 11 iPS19_82_iPS WT 14.19 14.19
## 12 iPS19_82_iPS WT 13.80 13.801.3.2 FGF9_iPS19-iPS-Mut
Input = ("
names values block
Mut 15.02 iPS19_82_iPS
Mut 15.12 iPS19_82_iPS
Mut 15.04 iPS19_82_iPS
Mut 14.46 iPS19_82_iPS
Mut 14.84 iPS19_82_iPS
Mut 14.56 iPS19_82_iPS
Mut 14.66 iPS19_82_iPS
Mut 14.54 iPS19_82_iPS
Mut 14.64 iPS19_82_iPS
Mut 14.34 iPS19_82_iPS
Mut 14.53 iPS19_82_iPS
Mut 14.56 iPS19_82_iPS
"
)
Data = read.table(textConnection(Input),header=TRUE)
Data$names = factor(Data$names,ordered=FALSE, levels=unique(Data$names))
Data$block = factor(Data$block,ordered=FALSE, levels=unique(Data$block))
# SRY_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data24 <- Data |>
mutate(
IQR = IQR(values, na.rm = TRUE),
Outlier_upper = quantile(values, probs = c(.75), na.rm = TRUE) + 1.5 * IQR,
Outlier_lower = quantile(values, probs = c(.25), na.rm = TRUE) - 1.5 * IQR,
values_wo_outliers = if_else(values <= Outlier_lower | values >= Outlier_upper, NA, values))
boxplot(values_wo_outliers ~ names, Data24)
Data24b<- Data24|> select(block, names, values, values_wo_outliers)
Data24b## block names values values_wo_outliers
## 1 iPS19_82_iPS Mut 15.02 15.02
## 2 iPS19_82_iPS Mut 15.12 15.12
## 3 iPS19_82_iPS Mut 15.04 15.04
## 4 iPS19_82_iPS Mut 14.46 14.46
## 5 iPS19_82_iPS Mut 14.84 14.84
## 6 iPS19_82_iPS Mut 14.56 14.56
## 7 iPS19_82_iPS Mut 14.66 14.66
## 8 iPS19_82_iPS Mut 14.54 14.54
## 9 iPS19_82_iPS Mut 14.64 14.64
## 10 iPS19_82_iPS Mut 14.34 14.34
## 11 iPS19_82_iPS Mut 14.53 14.53
## 12 iPS19_82_iPS Mut 14.56 14.56