library(ggplot2)
library(knitr)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(readxl)
library(renz)
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ lubridate 1.9.3 ✔ tibble 3.2.1
## ✔ purrr 1.0.2 ✔ tidyr 1.3.1
## ✔ readr 2.1.5
## ── 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 errors
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/human_crch_1.xlsx"
data <- read_excel(file_path)
data_long <- data %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 0.5 μM Human CrAT Test, 23°C (1)",
color = "Sample") +
theme_minimal()
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/human_crch_2.xlsx"
data <- read_excel(file_path)
data_long <- data %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 0.5 μM Human CrAT Test, 23°C",
color = "Sample") +
theme_minimal()
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/human_23.xlsx"
data <- read_excel(file_path)
data_long <- data %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; Human CrAT Test, 23°C",
color = "Sample") +
theme_minimal()
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/human_30.xlsx"
data <- read_excel(file_path)
data_long <- data %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; hCrAT Test, 30°C",
color = "Sample") +
theme_minimal()
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/human_37.xlsx"
data <- read_excel(file_path)
data_long <- data %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; hCrAT Test, 37°C",
color = "Sample") +
theme_minimal()
hCRAT_KM <- data.frame(
s = c(0.5, 1, 1.5, 3),
v23 = c(20.1, 13.2, 15.6, 41.3), #0603
v30 = c(2.88, 27.90857143, 14.57142857, 48.72),
v37 = c(40.04571429, 11.58857143, 10.49142857, 45.39428571)
)
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(hCRAT_KM$s, hCRAT_KM$v23,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
plot(hCRAT_KM$s, hCRAT_KM$v30,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
plot(hCRAT_KM$s, hCRAT_KM$v37,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
wg_hCRAT_cr <- lb(hCRAT_KM[, c("s", "v23")], weighting = TRUE)
wg_hCRAT_cr <- lb(hCRAT_KM[, c("s", "v30")], weighting = TRUE)
wg_hCRAT_cr <- lb(hCRAT_KM[, c("s", "v37")], weighting = TRUE)
dir.MM(hCRAT_KM[ , c(1,2)], unit_v = "uM/min")
## $parameters
## Km Vm
## 14.045 225.381
##
## $data
## S v fitted_v
## 1 0.5 20.1 7.747714
## 2 1.0 13.2 14.980459
## 3 1.5 15.6 21.747925
## 4 3.0 41.3 39.668114
dir.MM(hCRAT_KM[ , c(1,3)], unit_v = "uM/min")
## $parameters
## Km Vm
## -44.544 -663.293
##
## $data
## S v fitted_v
## 1 0.5 2.88000 7.529891
## 2 1.0 27.90857 15.232707
## 3 1.5 14.57143 23.114476
## 4 3.0 48.72000 47.898108
dir.MM(hCRAT_KM[ , c(1, 4)], unit_v = "uM/min")
## $parameters
## Km Vm
## -0.228 19.693
##
## $data
## S v fitted_v
## 1 0.5 40.04571 36.20037
## 2 1.0 11.58857 25.50907
## 3 1.5 10.49143 23.22288
## 4 3.0 45.39429 21.31277
if (!require(readxl)) install.packages("readxl")
if (!require(tidyverse)) install.packages("tidyverse")
library(readxl)
library(tidyverse)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/human_0803.xlsx"
data <- read_excel(file_path)
data_long <- data %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance VS Time; 0.5 μM hCrAT, 23 °C",
color = "Sample") +
theme_minimal()
hCRAT_cr1 <- data.frame(s <- c(0.01, 0.05, 0.1, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 3),
v <- c(7.1, 8.4, 12.7, 35.8, 51, 67.2, 68.8, 62.4, 62, 65, 45))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(hCRAT_cr1$s, hCRAT_cr1$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(hCRAT_cr1[ , c(1,2)], unit_v = "uM/min")
## $parameters
## Km Vm
## 0.210 70.139
##
## $data
## S v fitted_v
## 1 0.01 7.1 3.188136
## 2 0.05 8.4 13.488269
## 3 0.10 12.7 22.625484
## 4 0.25 35.8 38.119022
## 5 0.50 51.0 49.393662
## 6 0.75 67.2 54.796094
## 7 1.00 68.8 57.966116
## 8 1.25 62.4 60.050514
## 9 1.50 62.0 61.525439
## 10 1.75 65.0 62.624107
## 11 3.00 45.0 65.550467
g <- lb(hCRAT_cr1[ , c(1,2)])
wg <- lb(hCRAT_cr1[ , c(1,2)], weighting = TRUE)
ecb <- ecb(hCRAT_cr1[ , c(1,2)], unit_v = "uM/min")
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/human_1203_1.xlsx"
data <- read_excel(file_path)
data_long <- data %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; Human CrAT & carnitine, 23°C (2)",
color = "Sample") +
theme_minimal()
hCRAT_cr2 <- data.frame(s <- c(0.01, 0.05, 0.1, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 3),
v <- c(16.6, 24.4, 10.25, 54, 49, 76.3, 40, 97.4, 17.3, 90.7, 138))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(hCRAT_cr2$s, hCRAT_cr2$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(hCRAT_cr2[ , c(1,2)], unit_v = "uM/min")
## $parameters
## Km Vm
## 1.699 176.323
##
## $data
## S v fitted_v
## 1 0.01 16.60 1.031732
## 2 0.05 24.40 5.040680
## 3 0.10 10.25 9.801167
## 4 0.25 54.00 22.617111
## 5 0.50 49.00 40.091633
## 6 0.75 76.30 53.998469
## 7 1.00 40.00 65.329011
## 8 1.25 97.40 74.738471
## 9 1.50 17.30 82.677243
## 10 1.75 90.70 89.465135
## 11 3.00 138.00 112.570547
g <- lb(hCRAT_cr2[ , c(1,2)])
wg <- lb(hCRAT_cr2[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/human_1203_2.xlsx"
data <- read_excel(file_path)
data_long <- data %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 1.5) +
geom_line(size = 1) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; Human CrAT & carnitine, 23°C (3)",
color = "Sample") +
theme_minimal()
hCRAT_cr3 <- data.frame(s <- c(0.01, 0.05, 0.1, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 3),
v <- c(3.1, 5.4, 7.5, 75.2, 24, 102.4, 84, 33, 34.3, 90.4, 112.4))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(hCRAT_cr3$s, hCRAT_cr3$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(hCRAT_cr3[ , c(1,2)], unit_v = "uM/min")
## $parameters
## Km Vm
## 0.329 92.476
##
## $data
## S v fitted_v
## 1 0.01 3.1 2.727906
## 2 0.05 5.4 12.200000
## 3 0.10 7.5 21.556177
## 4 0.25 75.2 39.929188
## 5 0.50 24.0 55.775633
## 6 0.75 102.4 64.278962
## 7 1.00 84.0 69.583145
## 8 1.25 33.0 73.207726
## 9 1.50 34.3 75.841443
## 10 1.75 90.4 77.841751
## 11 3.00 112.4 83.336738
g <- lb(hCRAT_cr3[ , c(1,2)])
wg <- lb(hCRAT_cr3[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/human_0603.xlsx"
data <- read_excel(file_path)
data_long <- data %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 1.5) +
geom_line(size = 1) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; Human CrAT & carnitine, 23°C (4)",
color = "Sample") +
theme_minimal()
hCRAT_cr4 <- data.frame(s <- c(0.01, 0.05, 0.1, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 3),
v <- c(2.09, 2.3, 1.7, 25.7, 21, 24.7, 25, 16.45, 69, 56, 60))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(hCRAT_cr4$s, hCRAT_cr4$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(hCRAT_cr4[ , c(1,2)], unit_v = "uM/min")
## $parameters
## Km Vm
## 2.348 114.527
##
## $data
## S v fitted_v
## 1 0.01 2.09 0.4856955
## 2 0.05 2.30 2.3879691
## 3 0.10 1.70 4.6783905
## 4 0.25 25.70 11.0206890
## 5 0.50 21.00 20.1065660
## 6 0.75 24.70 27.7260329
## 7 1.00 25.00 34.2075866
## 8 1.25 16.45 39.7884241
## 9 1.50 69.00 44.6441008
## 10 1.75 56.00 48.9073328
## 11 3.00 60.00 64.2447644
g <- lb(hCRAT_cr4[ , c(1,2)])
wg <- lb(hCRAT_cr4[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/capsa_0.1.xlsx"
data1 <- read_excel(file_path)
data_long1 <- data1 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long1, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 0.1 uM cCrAT Test, 23°C",
color = "Sample") +
theme_minimal()
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/capsa_0.5.xlsx"
data2 <- read_excel(file_path)
data_long2 <- data2 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long2, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 0.5 uM cCrAT Test, 23°C",
color = "Sample") +
theme_minimal()
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/capsa_1.xlsx"
data3 <- read_excel(file_path)
data_long3 <- data3 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long3, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 1 uM cCrAT Test, 23°C",
color = "Sample") +
theme_minimal()
ggplot(data_long2, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 0.5 uM cCrAT, 23°C",
color = "Sample") +
theme_minimal()
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/capsa_30C.xlsx"
data4 <- read_excel(file_path)
data_long4 <- data4 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long4, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 0.5 uM cCrAT, 30°C",
color = "Sample") +
theme_minimal()
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/capsa_cr1.xlsx"
data_cr1 <- read_excel(file_path)
data_long_cr1 <- data_cr1 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long_cr1, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 2 uM cCrAT & Carnitine, 23°C",
color = "Sample") +
theme_minimal()
cCRAT_cr1 <- data.frame(s <- c(0.75, 1, 1.5, 3, 4.5),
v <- c(14.9, 22.9, 28.7, 22.3, 33.6))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(cCRAT_cr1$s, cCRAT_cr1$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(cCRAT_cr1[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## 0.690 35.252
##
## $data
## S v fitted_v
## 1 0.75 14.9 18.36042
## 2 1.00 22.9 20.85917
## 3 1.50 28.7 24.14521
## 4 3.00 22.3 28.66016
## 5 4.50 33.6 30.56532
g <- lb(cCRAT_cr1[ , c(1,2)])
wg <- lb(cCRAT_cr1[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/capsa_cr2.xlsx"
data_cr2 <- read_excel(file_path)
data_long_cr2 <- data_cr2 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long_cr2, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 2 uM cCrAT & Carnitine, 25°C (1)",
color = "Sample") +
theme_minimal()
cCRAT_cr2 <- data.frame(s <- c(0.75, 1, 1.5, 3, 4.5),
v <- c(6.5, 9.4, 20.3, 11.3, 27.6))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(cCRAT_cr2$s, cCRAT_cr2$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(cCRAT_cr2[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## 2.713 37.665
##
## $data
## S v fitted_v
## 1 0.75 6.5 8.157306
## 2 1.00 9.4 10.144088
## 3 1.50 20.3 13.410278
## 4 3.00 11.3 19.778575
## 5 4.50 27.6 23.498198
g <- lb(cCRAT_cr2[ , c(1,2)])
wg <- lb(cCRAT_cr2[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/capsa_cr3.xlsx"
data_cr3 <- read_excel(file_path)
data_long_cr3 <- data_cr3 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long_cr3, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 2 uM cCrAT & Carnitine, 25°C (2)",
color = "Sample") +
theme_minimal()
cCRAT_cr3 <- data.frame(s <- c(0.75, 1, 1.5, 3, 4.5),
v <- c(19.8, 14.3, 39.5, 23, 38))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(cCRAT_cr3$s, cCRAT_cr3$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(cCRAT_cr3[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## 0.825 40.873
##
## $data
## S v fitted_v
## 1 0.75 19.8 19.46333
## 2 1.00 14.3 22.39616
## 3 1.50 39.5 26.36968
## 4 3.00 23.0 32.05725
## 5 4.50 38.0 34.54056
g <- lb(cCRAT_cr3[ , c(1,2)])
wg <- lb(cCRAT_cr3[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/capsa_ch1.xlsx"
data_ch1 <- read_excel(file_path)
data_long_ch1 <- data_ch1 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long_ch1, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 2 uM cCrAT & Choline, 23°C",
color = "Sample") +
theme_minimal()
cCRAT_ch1 <- data.frame(s <- c(0.75, 1, 1.5, 3, 4.5),
v <- c(74, 61, 95.6, 97.6, 132.7))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(cCRAT_ch1$s, cCRAT_ch1$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(cCRAT_ch1[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## 1.061 151.605
##
## $data
## S v fitted_v
## 1 0.75 74.0 62.78506
## 2 1.00 61.0 73.55895
## 3 1.50 95.6 88.79637
## 4 3.00 97.6 111.99581
## 5 4.50 132.7 122.67982
g <- lb(cCRAT_ch1[ , c(1,2)])
wg <- lb(cCRAT_ch1[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/capsa_ch2.xlsx"
data_ch2 <- read_excel(file_path)
data_long_ch2 <- data_ch2 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long_ch2, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 2 uM cCrAT & Choline, 25°C (1)",
color = "Sample") +
theme_minimal()
cCRAT_ch2 <- data.frame(s <- c(0.75, 1, 1.5, 3, 4.5),
v <- c(0.67, 1.5, 1.3, 1.6, 2.3))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(cCRAT_ch2$s, cCRAT_ch2$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(cCRAT_ch2[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## 1.676 2.915
##
## $data
## S v fitted_v
## 1 0.75 0.67 0.9011748
## 2 1.00 1.50 1.0893124
## 3 1.50 1.30 1.3767317
## 4 3.00 1.60 1.8701882
## 5 4.50 2.30 2.1239475
g <- lb(cCRAT_ch2[ , c(1,2)])
wg <- lb(cCRAT_ch2[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/capsa_ch3.xlsx"
data_ch3 <- read_excel(file_path)
data_long_ch3 <- data_ch3 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long_ch3, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 2 uM cCrAT & Choline, 25°C (2)",
color = "Sample") +
theme_minimal()
cCRAT_ch3 <- data.frame(s <- c(0.75, 1, 1.5, 3, 4.5),
v <- c(0.34, 0.94, 0.6, 1.2, 0.05))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(cCRAT_ch3$s, cCRAT_ch3$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(cCRAT_ch3[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## 0.027 0.638
##
## $data
## S v fitted_v
## 1 0.75 0.34 0.6158301
## 2 1.00 0.94 0.6212269
## 3 1.50 0.60 0.6267191
## 4 3.00 1.20 0.6323092
## 5 4.50 0.05 0.6341948
g <- lb(cCRAT_ch3[ , c(1,2)])
wg <- lb(cCRAT_ch3[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/hydra_0.5.xlsx"
data1 <- read_excel(file_path)
data_long1 <- data1 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long1, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 0.5 uM hvCrAT Test, 22°C",
color = "Sample") +
theme_minimal()
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/hydra_1.xlsx"
data2 <- read_excel(file_path)
data_long2 <- data2 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long2, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 1 uM hvCrAT Test, 22°C",
color = "Sample") +
theme_minimal()
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/hydra_cr1.xlsx"
data_cr1 <- read_excel(file_path)
data_long_cr1 <- data_cr1 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long_cr1, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 1 uM hvCrAT & Carnitine, 22°C",
color = "Sample") +
theme_minimal()
hvCRAT_cr1 <- data.frame(s <- c(0.75, 1.5, 3),
v <- c(2, 2.4, 3.7))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(hvCRAT_cr1$s, hvCRAT_cr1$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(hvCRAT_cr1[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## 1.532 5.429
##
## $data
## S v fitted_v
## 1 0.75 2.0 1.784290
## 2 1.50 2.4 2.685851
## 3 3.00 3.7 3.593778
g <- lb(hvCRAT_cr1[ , c(1,2)])
wg <- lb(hvCRAT_cr1[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/hydra_cr2.xlsx"
data_cr2 <- read_excel(file_path)
data_long_cr2 <- data_cr2 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long_cr2, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 2 uM hvCrAT & Carnitine, 37°C (1)",
color = "Sample") +
theme_minimal()
hvCRAT_cr2 <- data.frame(s <- c(0.75, 1, 1.5, 3, 4.5),
v <- c(-3.8, 3.37, 2.47, 5, 4.5))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(hvCRAT_cr2$s, hvCRAT_cr2$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(hvCRAT_cr2[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## -0.857 0.640
##
## $data
## S v fitted_v
## 1 0.75 -3.80 -4.4859813
## 2 1.00 3.37 4.4755245
## 3 1.50 2.47 1.4930016
## 4 3.00 5.00 0.8959403
## 5 4.50 4.50 0.7905572
g <- lb(hvCRAT_cr2[ , c(1,2)])
wg <- lb(hvCRAT_cr2[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/hydra_cr3.xlsx"
data_cr3 <- read_excel(file_path)
data_long_cr3 <- data_cr3 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long_cr3, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 2 uM hvCrAT & Carnitine, 37°C (2)",
color = "Sample") +
theme_minimal()
hvCRAT_cr3 <- data.frame(s <- c(0.75, 1, 1.5, 3, 4.5),
v <- c(38.2, 6.7, 31.2, -46.7, 31.8))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(hvCRAT_cr3$s, hvCRAT_cr3$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(hvCRAT_cr3[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## -1.948 -8.871
##
## $data
## S v fitted_v
## 1 0.75 38.2 5.553631
## 2 1.00 6.7 9.357595
## 3 1.50 31.2 29.702009
## 4 3.00 -46.7 -25.297529
## 5 4.50 31.8 -15.642437
g <- lb(hvCRAT_cr3[ , c(1,2)])
wg <- lb(hvCRAT_cr3[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/hydra_ch1.xlsx"
data_ch1 <- read_excel(file_path)
data_long_ch1 <- data_ch1 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long_ch1, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 1 uM hvCrAT & Choline, 22°C",
color = "Sample") +
theme_minimal()
hvCRAT_ch1 <- data.frame(s <- c(0.75, 1.5, 3),
v <- c(-2.1, 1.6, 1.2))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(hvCRAT_ch1$s, hvCRAT_ch1$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(hvCRAT_ch1[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## -0.966 0.613
##
## $data
## S v fitted_v
## 1 0.75 -2.1 -2.1284722
## 2 1.50 1.6 1.7219101
## 3 3.00 1.2 0.9041298
g <- lb(hvCRAT_ch1[ , c(1,2)])
wg <- lb(hvCRAT_ch1[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/hydra_ch2.xlsx"
data_ch2 <- read_excel(file_path)
data_long_ch2 <- data_ch2 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long_ch2, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 2 uM hvCrAT & Choline, 37°C (1)",
color = "Sample") +
theme_minimal()
hvCRAT_ch2 <- data.frame(s <- c(0.75, 1, 1.5, 3, 4.5),
v <- c(-1.1, -1.7, -4.3, -1.5, 2.3))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(hvCRAT_ch2$s, hvCRAT_ch2$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(hvCRAT_ch2[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## -1.611 0.321
##
## $data
## S v fitted_v
## 1 0.75 -1.1 -0.2796167
## 2 1.00 -1.7 -0.5253682
## 3 1.50 -4.3 -4.3378378
## 4 3.00 -1.5 0.6933045
## 5 4.50 2.3 0.5000000
g <- lb(hvCRAT_ch2[ , c(1,2)])
wg <- lb(hvCRAT_ch2[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/hydra_ch3.xlsx"
data_ch3 <- read_excel(file_path)
data_long_ch3 <- data_ch3 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long_ch3, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 2 uM hvCrAT & Choline, 37°C (2)",
color = "Sample") +
theme_minimal()
hvCRAT_ch3 <- data.frame(s <- c(0.75, 1, 1.5, 3, 4.5),
v <- c(-45.9, -73, -44.4, -70.6, -48))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(hvCRAT_ch3$s, hvCRAT_ch3$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(hvCRAT_ch3[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## 0.048 -58.300
##
## $data
## S v fitted_v
## 1 0.75 -45.9 -54.79323
## 2 1.00 -73.0 -55.62977
## 3 1.50 -44.4 -56.49225
## 4 3.00 -70.6 -57.38189
## 5 4.50 -48.0 -57.68470
g <- lb(hvCRAT_ch3[ , c(1,2)])
wg <- lb(hvCRAT_ch3[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/platy_cr.xlsx"
data1 <- read_excel(file_path)
data_long1 <- data1 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long1, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 1 uM pdChAT & Carnitine, 25°C",
color = "Sample") +
theme_minimal()
pdCHAT_cr <- data.frame(s <- c(0.75, 1.5, 3),
v <- c(4.4, -7.7, -7.6))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(pdCHAT_cr$s, pdCHAT_cr$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(pdCHAT_cr[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## -1.088 -2.410
##
## $data
## S v fitted_v
## 1 0.75 4.4 5.347633
## 2 1.50 -7.7 -8.774272
## 3 3.00 -7.6 -3.781381
g <- lb(pdCHAT_cr[ , c(1,2)])
wg <- lb(pdCHAT_cr[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/platy_ch.xlsx"
data2 <- read_excel(file_path)
data_long2 <- data2 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long2, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.2) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 1 uM pdChAT & Choline, 25°C",
color = "Sample") +
theme_minimal()
pdCHAT_ch <- data.frame(s <- c(0.75, 1.5, 3),
v <- c(4.3, 4.4, 5.3))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(pdCHAT_ch$s, pdCHAT_ch$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(pdCHAT_ch[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## 0.248 5.526
##
## $data
## S v fitted_v
## 1 0.75 4.3 4.152806
## 2 1.50 4.4 4.741991
## 3 3.00 5.3 5.104064
g <- lb(pdCHAT_ch[ , c(1,2)])
wg <- lb(pdCHAT_ch[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/platy_ch1.xlsx"
data2 <- read_excel(file_path)
data_long2 <- data2 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long2, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 1 uM pdChAT & Choline, 25°C",
color = "Sample") +
theme_minimal()
pdCHAT_ch1 <- data.frame(
s = c(0.75, 1.5, 3),
v1 = c(4.11, 6.48, 6.72),
v2 = c(5.2, 7.356, 8.0173),
v3 = c(6.284, 5.274, 10.4763))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(pdCHAT_ch1$s, pdCHAT_ch1$v1,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
plot(pdCHAT_ch1$s, pdCHAT_ch1$v2,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
plot(pdCHAT_ch1$s, pdCHAT_ch1$v2,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
wh_pdCHAT_ch1 <- lb(pdCHAT_ch1[, c("s", "v1")], weighting = TRUE)
wg_pdCHAT_ch1 <- lb(pdCHAT_ch1[, c("s", "v2")], weighting = TRUE)
wg_pdCHAT_ch1 <- lb(pdCHAT_ch1[, c("s", "v3")], weighting = TRUE)
dir.MM(pdCHAT_ch1[ , c(1,2)], unit_v = "uM/min")
## $parameters
## Km Vm
## 0.705 8.647
##
## $data
## S v fitted_v
## 1 0.75 4.11 4.457216
## 2 1.50 6.48 5.882313
## 3 3.00 6.72 7.001619
dir.MM(pdCHAT_ch1[ , c(1,3)], unit_v = "uM/min")
## $parameters
## Km Vm
## 0.624 9.898
##
## $data
## S v fitted_v
## 1 0.75 5.2000 5.402838
## 2 1.50 7.3560 6.990113
## 3 3.00 8.0173 8.193709
dir.MM(pdCHAT_ch1[ , c(1,4)], unit_v = "uM/min")
## $parameters
## Km Vm
## 1.594 14.937
##
## $data
## S v fitted_v
## 1 0.75 6.2840 4.779330
## 2 1.50 5.2740 7.241597
## 3 3.00 10.4763 9.754245
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/zebrafish_cr.xlsx"
data1 <- read_excel(file_path)
data_long1 <- data1 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long1, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 1 uM drChAT & Carnitine, 25°C",
color = "Sample") +
theme_minimal()
drCHAT_cr <- data.frame(s <- c(0.75, 1.5, 3),
v <- c(1.79, 1.04, 1.44))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(drCHAT_cr$s, drCHAT_cr$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(drCHAT_cr[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## -0.280 1.085
##
## $data
## S v fitted_v
## 1 0.75 1.79 1.731383
## 2 1.50 1.04 1.334016
## 3 3.00 1.44 1.196691
g <- lb(drCHAT_cr[ , c(1,2)])
wg <- lb(drCHAT_cr[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/zebrafish_ch.xlsx"
data2 <- read_excel(file_path)
data_long2 <- data2 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long2, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 1 uM drChAT & Choline, 25°C",
color = "Sample") +
theme_minimal()
drCHAT_ch <- data.frame(s <- c(0.75, 1.5, 3),
v <- c(1.89, 2.62, 4.74))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(drCHAT_ch$s, drCHAT_ch$v,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
dir.MM(drCHAT_ch[ , c(1,2)], unit_v = "mM/min")
## $parameters
## Km Vm
## 5.032 12.519
##
## $data
## S v fitted_v
## 1 0.75 1.89 1.623876
## 2 1.50 2.62 2.874847
## 3 3.00 4.74 4.675921
g <- lb(drCHAT_ch[ , c(1,2)])
wg <- lb(drCHAT_ch[ , c(1,2)], weighting = TRUE)
file_path <- "C:/Users/sides/Documents/EMBL/Enzymes/zebrafish_ch1.xlsx"
data2 <- read_excel(file_path)
data_long2 <- data2 %>%
pivot_longer(cols = -Time, names_to = "Sample", values_to = "Value")
ggplot(data_long2, aes(x = Time, y = Value, color = Sample, group = Sample)) +
geom_point(size = 2) +
geom_line(size = 1.5) +
labs(x = "Time", y = "Absorbance", title = "Absorbance vs. Time; 1 uM drChAT & Choline, 25°C",
color = "Sample") +
theme_minimal()
drCHAT_ch1 <- data.frame(
s = c(0.75, 1.5, 3),
v1 = c(5.451429, 2.537143, 16.56),
v2 = c(3.5644, 7.26478, 18.2873),
v3 = c(10.3746, 8.387, 20.687368))
oldmar <- par()$mar
oldmfrow <- par()$mfrow
par(mfrow = c(1, 1))
par(mar = c(4, 4, 1, 1))
plot(drCHAT_ch1$s, drCHAT_ch1$v1,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
plot(drCHAT_ch1$s, drCHAT_ch1$v2,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
plot(drCHAT_ch1$s, drCHAT_ch1$v2,
type = 'p', ylab = 'v (uM/min)', xlab = '[s] (mM)',
pch = 21, bg = 'blue', col = 'black')
par(mar = oldmar)
par(mfrow = oldmfrow)
wh_drCHAT_ch1 <- lb(drCHAT_ch1[, c("s", "v1")], weighting = TRUE)
wg_drCHAT_ch1 <- lb(drCHAT_ch1[, c("s", "v2")], weighting = TRUE)
wg_drCHAT_ch1 <- lb(drCHAT_ch1[, c("s", "v3")], weighting = TRUE)
