if(!require(pacman))
  install.packages("pacman")
## Loading required package: pacman
library("pacman")
p_load("vroom",
       "dplyr",
       "ggplot2",
       "tidyr",
       "ggrepel",
       "plotly")
Melting_curve <-vroom (file= "https://raw.githubusercontent.com/ManuelLaraMVZ/resultados_PCR_practica/refs/heads/main/Disoci_ejemplo1.csv")
## Rows: 55 Columns: 6
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (6): Temperature, A1, B1, C1, D1, E1
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Melting_curve
## # A tibble: 55 Ɨ 6
##    Temperature    A1    B1    C1    D1     E1
##          <dbl> <dbl> <dbl> <dbl> <dbl>  <dbl>
##  1        65    1.96  1.98  2.11  2.11 0.0869
##  2        65.5  1.94  1.99  2.06  2.08 0.0834
##  3        66    1.89  1.93  2.03  2.07 0.0932
##  4        66.5  1.86  1.89  1.98  2.02 0.0676
##  5        67    1.82  1.89  1.94  1.98 0.0738
##  6        67.5  1.77  1.83  1.90  1.93 0.0766
##  7        68    1.74  1.78  1.86  1.87 0.0686
##  8        68.5  1.70  1.76  1.79  1.84 0.0689
##  9        69    1.65  1.71  1.79  1.80 0.0665
## 10        69.5  1.60  1.64  1.75  1.76 0.0744
## # ℹ 45 more rows
Melting_curve2 <- Melting_curve %>% 
mutate(Temperatura=Temperature,DDR=A1,JRWF=B1,PPOF=C1,MLL=D1,H2O=E1)%>%
  select(-Temperature:-E1)
  
Melting_curve2
## # A tibble: 55 Ɨ 6
##    Temperatura   DDR  JRWF  PPOF   MLL    H2O
##          <dbl> <dbl> <dbl> <dbl> <dbl>  <dbl>
##  1        65    1.96  1.98  2.11  2.11 0.0869
##  2        65.5  1.94  1.99  2.06  2.08 0.0834
##  3        66    1.89  1.93  2.03  2.07 0.0932
##  4        66.5  1.86  1.89  1.98  2.02 0.0676
##  5        67    1.82  1.89  1.94  1.98 0.0738
##  6        67.5  1.77  1.83  1.90  1.93 0.0766
##  7        68    1.74  1.78  1.86  1.87 0.0686
##  8        68.5  1.70  1.76  1.79  1.84 0.0689
##  9        69    1.65  1.71  1.79  1.80 0.0665
## 10        69.5  1.60  1.64  1.75  1.76 0.0744
## # ℹ 45 more rows
Melting_curve3 <- Melting_curve2 %>% 
  pivot_longer(cols = -Temperatura,
               names_to = "Muestras",
               values_to = "Fluorescencia")
Melting_curve3
## # A tibble: 275 Ɨ 3
##    Temperatura Muestras Fluorescencia
##          <dbl> <chr>            <dbl>
##  1        65   DDR             1.96  
##  2        65   JRWF            1.98  
##  3        65   PPOF            2.11  
##  4        65   MLL             2.11  
##  5        65   H2O             0.0869
##  6        65.5 DDR             1.94  
##  7        65.5 JRWF            1.99  
##  8        65.5 PPOF            2.06  
##  9        65.5 MLL             2.08  
## 10        65.5 H2O             0.0834
## # ℹ 265 more rows
Grafica_melting <- ggplot(Melting_curve3,
                          aes(x = Temperatura,
                                        y = Fluorescencia,
                                        color = Muestras))+
  geom_line(linewidth=1.5)
Grafica_melting

Derivadas <- Melting_curve2 %>% 
  mutate(across(DDR:H2O,
                ~-c(NA, diff(.x)/diff(Melting_curve2$Temperatura)), .names ="d_{.col}")) %>% 
  select(-DDR: -H2O) %>% 
  slice(-1)

Derivadas
## # A tibble: 54 Ɨ 6
##    Temperatura  d_DDR   d_JRWF   d_PPOF  d_MLL     d_H2O
##          <dbl>  <dbl>    <dbl>    <dbl>  <dbl>     <dbl>
##  1        65.5 0.0365 -0.0147   0.0940  0.0711  0.00703 
##  2        66   0.102   0.108    0.0614  0.0146 -0.0197  
##  3        66.5 0.0695  0.0883   0.112   0.108   0.0512  
##  4        67   0.0652  0.00898  0.0646  0.0772 -0.0123  
##  5        67.5 0.109   0.114    0.0903  0.0923 -0.00567 
##  6        68   0.0666  0.0994   0.0707  0.122   0.0162  
##  7        68.5 0.0774  0.0335   0.139   0.0558 -0.000754
##  8        69   0.0860  0.0979  -0.00165 0.0850  0.00488 
##  9        69.5 0.111   0.146    0.0908  0.0844 -0.0159  
## 10        70   0.0582  0.0279   0.130   0.0864  0.00967 
## # ℹ 44 more rows
Derivadas2 <- Derivadas%>% 
  pivot_longer(cols = -Temperatura,
               names_to = "Muestras",
               values_to = "Derivadas")
Derivadas2
## # A tibble: 270 Ɨ 3
##    Temperatura Muestras Derivadas
##          <dbl> <chr>        <dbl>
##  1        65.5 d_DDR      0.0365 
##  2        65.5 d_JRWF    -0.0147 
##  3        65.5 d_PPOF     0.0940 
##  4        65.5 d_MLL      0.0711 
##  5        65.5 d_H2O      0.00703
##  6        66   d_DDR      0.102  
##  7        66   d_JRWF     0.108  
##  8        66   d_PPOF     0.0614 
##  9        66   d_MLL      0.0146 
## 10        66   d_H2O     -0.0197 
## # ℹ 260 more rows
Grafica_derivada <-ggplot(Derivadas2,
                            aes(x = Temperatura,
                                y = Derivadas,
                              color = Muestras)) +
  geom_line(linewidth=1.5)+
  theme_classic()+
  labs(title = "Curvas de la derivada de disociación RT-qPCR",
       subtitle = "Todas las muestras",
       caption = "Diseñó:Paola López",
       x = "Temperatura (°C)",
       y = expression("-" * Delta * "F/" * Delta * "T"))+
  theme(axis.line = element_line(size = 1.2, color = "black"),
    axis.title = element_text(face = "bold"),              
    axis.text = element_text(face = "bold"))+
  scale_x_continuous(breaks=seq(min(Derivadas2$Temperatura),
                                max(Derivadas2$Temperatura),
                                by = 2.5))
## Warning: The `size` argument of `element_line()` is deprecated as of ggplot2 3.4.0.
## ℹ Please use the `linewidth` argument instead.
## This warning is displayed once per session.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
Grafica_derivada

Grafica_derivada_3D <- plot_ly(Derivadas2,
                    x = ~Temperatura,
                    y = ~Muestras,
                    z = ~Derivadas,
                    color = ~factor(Muestras),
                    type = "scatter3d",
                    mode = "lines",
                    line = list(width = 6)) %>% 
  layout(title= "Curva de derivada en 3D",
         scene= list(
         xaxis=list(title="Temperatura"),
         yaxis=list(title="Muestras"),
         zaxis=list(title="-dT/dF")))

Grafica_derivada_3D
Grafica_derivada_equipo <- ggplot(Derivadas,
                                  aes(x = Temperatura))+
  geom_line(aes(y=d_MLL,color="d_MLL"),linewidth = 1.5)+
  geom_line(aes(y=d_H2O,color="d_H2O"),linewidth = 1.5)+
  scale_color_manual(values=c("d_MLL"="#6287f1","d_H2O"="pink"))+
  theme_classic() +
  labs(title = "Derivada de disociación RT-qPCR",
       subtitle = "Tejido: Corteza de cerebro",
       caption = "Diseñó:Paola López",
       x = "Temperatura (° C)",
       y = expression(-Delta~F/Delta~T))+
  theme(
    axis.line = element_line(size = 1.2, color = "black"),
    axis.title = element_text(face = "bold"),              
    axis.text = element_text(face = "bold"),
    legend.title = element_text(face = "bold"),
    legend.text = element_text(face = "bold")) +
  scale_x_continuous(breaks = seq(min(Derivadas$Temperatura), max(Derivadas$Temperatura), by = 2.5))

Grafica_derivada_equipo

Pico <- max(Derivadas$d_MLL)
Pico
## [1] 0.738565
Tm <- Derivadas %>% 
    filter(d_MLL==Pico)%>% 
  select(Temperatura,d_MLL)
Tm
## # A tibble: 1 Ɨ 2
##   Temperatura d_MLL
##         <dbl> <dbl>
## 1          82 0.739
Grafica_derivada_equipo2 <- Grafica_derivada_equipo+
  geom_vline(xintercept=Tm$Temperatura,
             color="purple",
             linetype="dashed",
             linewidth=1)+
  geom_label_repel(data=Tm,
                   aes(x=Temperatura,
                       y=d_MLL,
                       label=paste("Tm=",round(Temperatura),"°C")),
                   nudge_x=4,
                   nudge_y=-0.03,
                   max.overlaps=100,
                   color="black",
                   fill="lightgreen")
  
Grafica_derivada_equipo2