Supplementary_Data_31
Denis
2023-07-10
RT-qPCR analysis - SOX9 - 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 SOX9
1.1 SOX9_iPS07
1.1.1 SOX9_iPS07-M1_36h00-Mut
Input = ("
names values block
Mut 7.68 iPS07-82-M1-1
Mut 8.32 iPS07-82-M1-2
Mut 7.92 iPS07-82-M1-3
Mut 7.32 iPS07-82-M1-4
Mut 7.47 iPS07-82-M1-5
"
)
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))
# SOX9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data1 <- 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, Data1)
Data1b<- Data1|> select(block, names, values, values_wo_outliers)
Data1b## block names values values_wo_outliers
## 1 iPS07-82-M1-1 Mut 7.68 7.68
## 2 iPS07-82-M1-2 Mut 8.32 8.32
## 3 iPS07-82-M1-3 Mut 7.92 7.92
## 4 iPS07-82-M1-4 Mut 7.32 7.32
## 5 iPS07-82-M1-5 Mut 7.47 7.471.1.2 SOX9_iPS07-M2_48h00-Wt
Input = ("
names values block
WT 5.11 iPS07-45-M2_48
WT 4.87 iPS07-45-M2_48
WT 5.08 iPS07-45-M2_48
WT 5.31 iPS07-45-M2_48
WT 4.97 iPS07-45-M2_48
"
)
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))
# SOX9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data2 <- 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, Data2)
Data2b<- Data2|> select(block, names, values, values_wo_outliers)
Data2b## block names values values_wo_outliers
## 1 iPS07-45-M2_48 WT 5.11 5.11
## 2 iPS07-45-M2_48 WT 4.87 4.87
## 3 iPS07-45-M2_48 WT 5.08 5.08
## 4 iPS07-45-M2_48 WT 5.31 5.31
## 5 iPS07-45-M2_48 WT 4.97 4.971.1.3 SOX9_iPS07-M2_48h00-Mut
Input = ("
names values block
Mut 5.73 iPS07-82-M2_48
Mut 8.82 iPS07-82-M2_48
Mut 8.48 iPS07-82-M2_48
Mut 6.00 iPS07-82-M2_48
Mut 7.42 iPS07-82-M2_48
"
)
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))
# SOX9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data3 <- 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, Data3)
Data3b<- Data3|> select(block, names, values, values_wo_outliers)
Data3b## block names values values_wo_outliers
## 1 iPS07-82-M2_48 Mut 5.73 5.73
## 2 iPS07-82-M2_48 Mut 8.82 8.82
## 3 iPS07-82-M2_48 Mut 8.48 8.48
## 4 iPS07-82-M2_48 Mut 6.00 6.00
## 5 iPS07-82-M2_48 Mut 7.42 7.421.2 SOX9_iPS09
1.2.1 SOX9_iPS09-M1_36h00-Wt
Input = ("
names values block
WT 8.98 iPS07-45-iPS
WT 12.25 iPS07-45-iPS
WT 11.26 iPS07-45-iPS
WT 5.93 iPS07-45-iPS
WT 7.69 iPS07-45-iPS
WT 6.80 iPS07-45-iPS
WT 6.58 iPS07-45-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))
# SOX9_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 iPS07-45-iPS WT 8.98 8.98
## 2 iPS07-45-iPS WT 12.25 12.25
## 3 iPS07-45-iPS WT 11.26 11.26
## 4 iPS07-45-iPS WT 5.93 5.93
## 5 iPS07-45-iPS WT 7.69 7.69
## 6 iPS07-45-iPS WT 6.80 6.80
## 7 iPS07-45-iPS WT 6.58 6.581.2.2 SOX9_iPS09-M1_36h00-Mut
Input = ("
names values block
Mut 7.90 iPS09-82-iPS
Mut 7.69 iPS09-82-iPS
Mut 7.52 iPS09-82-iPS
Mut 7.07 iPS09-82-iPS
Mut 8.41 iPS09-82-iPS
Mut 8.11 iPS09-82-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))
# SOX9_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-iPS Mut 7.90 7.90
## 2 iPS09-82-iPS Mut 7.69 7.69
## 3 iPS09-82-iPS Mut 7.52 7.52
## 4 iPS09-82-iPS Mut 7.07 7.07
## 5 iPS09-82-iPS Mut 8.41 8.41
## 6 iPS09-82-iPS Mut 8.11 8.111.2.3 SOX9_iPS09-M2_24h00-Wt
Input = ("
names values block
WT 7.16 iPS09-45-M1_36h00
WT 6.79 iPS09-45-M1_36h00
WT 7.02 iPS09-45-M1_36h00
WT 6.89 iPS09-45-M1_36h00
WT 7.13 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))
# SOX9_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-M1_36h00 WT 7.16 7.16
## 2 iPS09-45-M1_36h00 WT 6.79 6.79
## 3 iPS09-45-M1_36h00 WT 7.02 7.02
## 4 iPS09-45-M1_36h00 WT 6.89 6.89
## 5 iPS09-45-M1_36h00 WT 7.13 7.131.2.4 SOX9_iPS09-M2_24h00-Mut
Input = ("
names values block
Mut 6.51 iPS09-82-M1_36h00
Mut 6.39 iPS09-82-M1_36h00
Mut 6.22 iPS09-82-M1_36h00
Mut 6.22 iPS09-82-M1_36h00
Mut 6.14 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))
# SOX9_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-M1_36h00 Mut 6.51 6.51
## 2 iPS09-82-M1_36h00 Mut 6.39 6.39
## 3 iPS09-82-M1_36h00 Mut 6.22 6.22
## 4 iPS09-82-M1_36h00 Mut 6.22 6.22
## 5 iPS09-82-M1_36h00 Mut 6.14 6.141.2.5 SOX9_iPS09-M3_24h00-Wt
Input = ("
names values block
WT 7.07 iPS09-45-M2_24h00
WT 6.15 iPS09-45-M2_24h00
WT 6.86 iPS09-45-M2_24h00
WT 5.89 iPS09-45-M2_24h00
WT 5.81 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))
# SOX9_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-M2_24h00 WT 7.07 7.07
## 2 iPS09-45-M2_24h00 WT 6.15 6.15
## 3 iPS09-45-M2_24h00 WT 6.86 6.86
## 4 iPS09-45-M2_24h00 WT 5.89 5.89
## 5 iPS09-45-M2_24h00 WT 5.81 5.811.2.6 SOX9_iPS09-M3_48h00-Wt
Input = ("
names values block
Mut 5.88 iPS09-82-M2_24h00
Mut 6.04 iPS09-82-M2_24h00
Mut 5.87 iPS09-82-M2_24h00
Mut 5.89 iPS09-82-M2_24h00
Mut 6.08 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))
# SOX9_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 iPS09-82-M2_24h00 Mut 5.88 5.88
## 2 iPS09-82-M2_24h00 Mut 6.04 6.04
## 3 iPS09-82-M2_24h00 Mut 5.87 5.87
## 4 iPS09-82-M2_24h00 Mut 5.89 5.89
## 5 iPS09-82-M2_24h00 Mut 6.08 6.081.2.7 SOX9_iPS09-M3_48h00-Mut
Input = ("
names values block
WT 6.38 iPS09-45-M3_24h00
WT 5.33 iPS09-45-M3_24h00
WT 5.21 iPS09-45-M3_24h00
WT 4.68 iPS09-45-M3_24h00
WT 5.99 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))
# SOX9_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 iPS09-45-M3_24h00 WT 6.38 6.38
## 2 iPS09-45-M3_24h00 WT 5.33 5.33
## 3 iPS09-45-M3_24h00 WT 5.21 5.21
## 4 iPS09-45-M3_24h00 WT 4.68 4.68
## 5 iPS09-45-M3_24h00 WT 5.99 5.991.2.8 SOX9_iPS09-iPS-Wt
Input = ("
names values block
WT 5.26 iPS09-45-M3_48h00
WT 5.41 iPS09-45-M3_48h00
WT 5.20 iPS09-45-M3_48h00
WT 5.76 iPS09-45-M3_48h00
WT 6.47 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))
# SOX9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data11 <- 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, Data11)
Data11b<- Data11|> select(block, names, values, values_wo_outliers)
Data11b## block names values values_wo_outliers
## 1 iPS09-45-M3_48h00 WT 5.26 5.26
## 2 iPS09-45-M3_48h00 WT 5.41 5.41
## 3 iPS09-45-M3_48h00 WT 5.20 5.20
## 4 iPS09-45-M3_48h00 WT 5.76 5.76
## 5 iPS09-45-M3_48h00 WT 6.47 6.471.2.9 SOX9_iPS09-iPS-Mut
Input = ("
names values block
Mut 5.54 iPS09-82-M3_48h00
Mut 5.19 iPS09-82-M3_48h00
Mut 5.22 iPS09-82-M3_48h00
Mut 4.88 iPS09-82-M3_48h00
Mut 4.34 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))
# SOX9_boxplot 1
boxplot(values ~ names,
data = Data,
ylab ="values",
xlab ="names")
Data12 <- 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, Data12)
Data12b<- Data12|> select(block, names, values, values_wo_outliers)
Data12b## block names values values_wo_outliers
## 1 iPS09-82-M3_48h00 Mut 5.54 5.54
## 2 iPS09-82-M3_48h00 Mut 5.19 5.19
## 3 iPS09-82-M3_48h00 Mut 5.22 5.22
## 4 iPS09-82-M3_48h00 Mut 4.88 4.88
## 5 iPS09-82-M3_48h00 Mut 4.34 NA1.3 SOX9_iPS12
1.3.1 SOX9_iPS12-M1_36h00-Wt
Input = ("
names values block
WT 7.22 iPS12_45_M1_36_P
WT 7.41 iPS12_45_M1_36_P
WT 7.24 iPS12_45_M1_36_P
WT 7.03 iPS12_45_M1_36_P
WT 7.31 iPS12_45_M1_36_P
WT 7.72 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))
# SOX9_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 7.22 7.22
## 2 iPS12_45_M1_36_P WT 7.41 7.41
## 3 iPS12_45_M1_36_P WT 7.24 7.24
## 4 iPS12_45_M1_36_P WT 7.03 7.03
## 5 iPS12_45_M1_36_P WT 7.31 7.31
## 6 iPS12_45_M1_36_P WT 7.72 NA1.3.2 SOX9_iPS12-M1_36h00-Mut
Input = ("
names values block
Mut 6.15 iPS12_82_M1_36_P
Mut 6.17 iPS12_82_M1_36_P
Mut 6.18 iPS12_82_M1_36_P
Mut 6.23 iPS12_82_M1_36_P
Mut 6.69 iPS12_82_M1_36_P
Mut 6.28 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))
# SOX9_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 6.15 6.15
## 2 iPS12_82_M1_36_P Mut 6.17 6.17
## 3 iPS12_82_M1_36_P Mut 6.18 6.18
## 4 iPS12_82_M1_36_P Mut 6.23 6.23
## 5 iPS12_82_M1_36_P Mut 6.69 NA
## 6 iPS12_82_M1_36_P Mut 6.28 6.281.3.3 SOX9_iPS12-M2_06h00-Wt
Input = ("
names values block
WT 8.65 iPS12_45_M2_06_P
WT 9.41 iPS12_45_M2_06_P
WT 9.10 iPS12_45_M2_06_P
WT 9.97 iPS12_45_M2_06_P
WT 9.94 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))
# SOX9_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 8.65 8.65
## 2 iPS12_45_M2_06_P WT 9.41 9.41
## 3 iPS12_45_M2_06_P WT 9.10 9.10
## 4 iPS12_45_M2_06_P WT 9.97 9.97
## 5 iPS12_45_M2_06_P WT 9.94 9.94
## 6 iPS12_45_M2_06_P WT NA NA1.3.4 SOX9_iPS12-M2_06h00-Mut
Input = ("
names values block
Mut NA iPS12_82_M2_06_P
Mut 8.18 iPS12_82_M2_06_P
Mut 9.10 iPS12_82_M2_06_P
Mut 9.54 iPS12_82_M2_06_P
Mut 9.92 iPS12_82_M2_06_P
Mut 9.32 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))
# SOX9_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 NA NA
## 2 iPS12_82_M2_06_P Mut 8.18 NA
## 3 iPS12_82_M2_06_P Mut 9.10 9.10
## 4 iPS12_82_M2_06_P Mut 9.54 9.54
## 5 iPS12_82_M2_06_P Mut 9.92 9.92
## 6 iPS12_82_M2_06_P Mut 9.32 9.321.3.5 SOX9_iPS12-M2_12h00-Wt_vs_Mut
Input = ("
names values block
WT NA iPS12_45_M2_12_P
WT 9.02 iPS12_45_M2_12_P
WT 8.55 iPS12_45_M2_12_P
WT 10.87 iPS12_45_M2_12_P
WT 9.08 iPS12_45_M2_12_P
WT 8.92 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))
# SOX9_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 NA NA
## 2 iPS12_45_M2_12_P WT 9.02 9.02
## 3 iPS12_45_M2_12_P WT 8.55 NA
## 4 iPS12_45_M2_12_P WT 10.87 NA
## 5 iPS12_45_M2_12_P WT 9.08 9.08
## 6 iPS12_45_M2_12_P WT 8.92 8.921.3.6 SOX9_iPS12-M2_12h00-Mut
Input = ("
names values block
Mut 8.51 iPS12_82_M2_12_P
Mut 8.03 iPS12_82_M2_12_P
Mut 10.79 iPS12_82_M2_12_P
Mut 8.39 iPS12_82_M2_12_P
Mut 9.72 iPS12_82_M2_12_P
Mut 10.10 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))
# SOX9_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 8.51 8.51
## 2 iPS12_82_M2_12_P Mut 8.03 8.03
## 3 iPS12_82_M2_12_P Mut 10.79 10.79
## 4 iPS12_82_M2_12_P Mut 8.39 8.39
## 5 iPS12_82_M2_12_P Mut 9.72 9.72
## 6 iPS12_82_M2_12_P Mut 10.10 10.101.3.7 SOX9_iPS12_M2_24h00-Wt
Input = ("
names values block
WT 6.35 iPS12_45_M2_24_P
WT 7.32 iPS12_45_M2_24_P
WT 6.42 iPS12_45_M2_24_P
WT 6.71 iPS12_45_M2_24_P
WT 6.63 iPS12_45_M2_24_P
WT 10.74 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))
# SOX9_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 6.35 6.35
## 2 iPS12_45_M2_24_P WT 7.32 7.32
## 3 iPS12_45_M2_24_P WT 6.42 6.42
## 4 iPS12_45_M2_24_P WT 6.71 6.71
## 5 iPS12_45_M2_24_P WT 6.63 6.63
## 6 iPS12_45_M2_24_P WT 10.74 NA1.3.8 SOX9_iPS12_M2_24h00-Mut
Input = ("
names values block
Mut 8.24 iPS12_82_M2_24_P
Mut 7.83 iPS12_82_M2_24_P
Mut 7.47 iPS12_82_M2_24_P
Mut 8.12 iPS12_82_M2_24_P
Mut 7.52 iPS12_82_M2_24_P
Mut 9.68 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))
# SOX9_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 8.24 8.24
## 2 iPS12_82_M2_24_P Mut 7.83 7.83
## 3 iPS12_82_M2_24_P Mut 7.47 7.47
## 4 iPS12_82_M2_24_P Mut 8.12 8.12
## 5 iPS12_82_M2_24_P Mut 7.52 7.52
## 6 iPS12_82_M2_24_P Mut 9.68 NA1.3.9 SOX9_iPS12-M2_48h00-Wt
Input = ("
names values block
WT 5.42 iPS12_45_M2_48_P
WT 6.85 iPS12_45_M2_48_P
WT 7.00 iPS12_45_M2_48_P
WT 6.71 iPS12_45_M2_48_P
WT 6.94 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))
# SOX9_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 5.42 NA
## 2 iPS12_45_M2_48_P WT 6.85 6.85
## 3 iPS12_45_M2_48_P WT 7.00 7.00
## 4 iPS12_45_M2_48_P WT 6.71 6.71
## 5 iPS12_45_M2_48_P WT 6.94 6.94
## 6 iPS12_45_M2_48_P WT NA NA1.3.10 SOX9_iPS12-M2_48h00-Mut
Input = ("
names values block
Mut 6.15 iPS12_82_M2_48_P
Mut 6.56 iPS12_82_M2_48_P
Mut 7.01 iPS12_82_M2_48_P
Mut 6.19 iPS12_82_M2_48_P
Mut 6.81 iPS12_82_M2_48_P
Mut 7.09 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))
# SOX9_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 6.15 6.15
## 2 iPS12_82_M2_48_P Mut 6.56 6.56
## 3 iPS12_82_M2_48_P Mut 7.01 7.01
## 4 iPS12_82_M2_48_P Mut 6.19 6.19
## 5 iPS12_82_M2_48_P Mut 6.81 6.81
## 6 iPS12_82_M2_48_P Mut 7.09 7.091.4 SOX9_iPS19
1.4.1 SOX9_iPS19-iPS-Wt
Input = ("
names values block
WT 8.73 iPS19_45_iPS
WT 7.88 iPS19_45_iPS
WT 7.92 iPS19_45_iPS
WT 7.80 iPS19_45_iPS
WT 7.60 iPS19_45_iPS
WT 7.65 iPS19_45_iPS
WT 7.12 iPS19_82_iPS
WT 8.39 iPS19_82_iPS
WT 7.88 iPS19_82_iPS
WT 9.05 iPS19_82_iPS
WT 7.92 iPS19_82_iPS
WT 7.25 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 8.73 NA
## 2 iPS19_45_iPS WT 7.88 7.88
## 3 iPS19_45_iPS WT 7.92 7.92
## 4 iPS19_45_iPS WT 7.80 7.80
## 5 iPS19_45_iPS WT 7.60 7.60
## 6 iPS19_45_iPS WT 7.65 7.65
## 7 iPS19_82_iPS WT 7.12 7.12
## 8 iPS19_82_iPS WT 8.39 8.39
## 9 iPS19_82_iPS WT 7.88 7.88
## 10 iPS19_82_iPS WT 9.05 NA
## 11 iPS19_82_iPS WT 7.92 7.92
## 12 iPS19_82_iPS WT 7.25 7.251.4.2 SOX9_iPS19-iPS-Mut
Input = ("
names values block
Mut 7.70 iPS19_82_iPS
Mut 7.81 iPS19_82_iPS
Mut 8.32 iPS19_82_iPS
Mut 7.99 iPS19_82_iPS
Mut 8.29 iPS19_82_iPS
Mut 8.00 iPS19_82_iPS
Mut 7.79 iPS19_82_iPS
Mut 9.24 iPS19_82_iPS
Mut 8.00 iPS19_82_iPS
Mut 8.18 iPS19_82_iPS
Mut 8.35 iPS19_82_iPS
Mut 8.75 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 7.70 7.70
## 2 iPS19_82_iPS Mut 7.81 7.81
## 3 iPS19_82_iPS Mut 8.32 8.32
## 4 iPS19_82_iPS Mut 7.99 7.99
## 5 iPS19_82_iPS Mut 8.29 8.29
## 6 iPS19_82_iPS Mut 8.00 8.00
## 7 iPS19_82_iPS Mut 7.79 7.79
## 8 iPS19_82_iPS Mut 9.24 NA
## 9 iPS19_82_iPS Mut 8.00 8.00
## 10 iPS19_82_iPS Mut 8.18 8.18
## 11 iPS19_82_iPS Mut 8.35 8.35
## 12 iPS19_82_iPS Mut 8.75 8.75