if(!requireNamespace("pacman", quietly = F))
install.packages("pacman")
## Loading required namespace: pacman
library("pacman")
p_load("vroom",
"dplyr",
"ggplot2")
Datos_PCR <- vroom(file = "https://raw.githubusercontent.com/ManuelLaraMVZ/Metabolomica_2026_1/refs/heads/main/Cts")
## Rows: 20 Columns: 5
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (4): Well, Grupo, Practica, Fluor
## dbl (1): Cq
##
## 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.
Datos_PCR
## # A tibble: 20 × 5
## Well Grupo Practica Fluor Cq
## <chr> <chr> <chr> <chr> <dbl>
## 1 50 Curva Absoluta SYBR 5.15
## 2 10 Curva Absoluta SYBR 10.8
## 3 5 Curva Absoluta SYBR 13.9
## 4 1 Curva Absoluta SYBR 15.7
## 5 0.5 Curva Absoluta SYBR 16.5
## 6 0.1 Curva Absoluta SYBR 18.3
## 7 Muestra G1 Absoluta SYBR 11.5
## 8 Muestra G2 Absoluta SYBR 13.1
## 9 A01 G1 Relativa SYBR 28.6
## 10 A02 G1 Relativa SYBR 15.0
## 11 A03 G1 Relativa SYBR 14.0
## 12 A04 G1 Relativa SYBR 50
## 13 A05 G1 Relativa SYBR 15.5
## 14 A06 G1 Relativa SYBR 12.6
## 15 A01 G2 Relativa SYBR 12.7
## 16 A02 G2 Relativa SYBR 16.3
## 17 A03 G2 Relativa SYBR 13.1
## 18 Referencia Referencia Relativa SYBR 18.4
## 19 Profesor G1 Relativa SYBR 20.0
## 20 Profesor G2 Relativa SYBR 20.0
Filtrado <- Datos_PCR %>%
filter(Practica == "Relativa") %>%
filter(Grupo %in% c("G1", "G2")) %>%
select(Well, Grupo, Cq)
Filtrado
## # A tibble: 11 × 3
## Well Grupo Cq
## <chr> <chr> <dbl>
## 1 A01 G1 28.6
## 2 A02 G1 15.0
## 3 A03 G1 14.0
## 4 A04 G1 50
## 5 A05 G1 15.5
## 6 A06 G1 12.6
## 7 A01 G2 12.7
## 8 A02 G2 16.3
## 9 A03 G2 13.1
## 10 Profesor G1 20.0
## 11 Profesor G2 20.0
Referencia <- Datos_PCR %>%
filter(Practica == "Relativa") %>%
filter(Grupo == "Referencia") %>%
select(Well, Cq)
Referencia
## # A tibble: 1 × 2
## Well Cq
## <chr> <dbl>
## 1 Referencia 18.4
Ref_prom <- mean(Referencia$Cq, na.rm = TRUE)
Dos_DCt <- Filtrado %>%
mutate(
DCt = Cq - Ref_prom,
DosDCt = 2^(-DCt)
)
Dos_DCt
## # A tibble: 11 × 5
## Well Grupo Cq DCt DosDCt
## <chr> <chr> <dbl> <dbl> <dbl>
## 1 A01 G1 28.6 10.1 8.83e- 4
## 2 A02 G1 15.0 -3.38 1.04e+ 1
## 3 A03 G1 14.0 -4.37 2.07e+ 1
## 4 A04 G1 50 31.6 3.08e-10
## 5 A05 G1 15.5 -2.93 7.64e+ 0
## 6 A06 G1 12.6 -5.77 5.44e+ 1
## 7 A01 G2 12.7 -5.71 5.22e+ 1
## 8 A02 G2 16.3 -2.09 4.26e+ 0
## 9 A03 G2 13.1 -5.31 3.96e+ 1
## 10 Profesor G1 20.0 1.64 3.20e- 1
## 11 Profesor G2 20.0 1.64 3.20e- 1
Control <- Dos_DCt %>%
filter(Grupo == "G1") %>%
summarise(control = mean(DosDCt, na.rm = TRUE)) %>%
pull(control)
Dos_DDCt <- Dos_DCt %>%
mutate(
DosDDCt = DosDCt / Control,
L2 = log2(DosDDCt)
)
Dos_DDCt
## # A tibble: 11 × 7
## Well Grupo Cq DCt DosDCt DosDDCt L2
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 A01 G1 28.6 10.1 8.83e- 4 6.61e- 5 -13.9
## 2 A02 G1 15.0 -3.38 1.04e+ 1 7.78e- 1 -0.363
## 3 A03 G1 14.0 -4.37 2.07e+ 1 1.55e+ 0 0.634
## 4 A04 G1 50 31.6 3.08e-10 2.31e-11 -35.3
## 5 A05 G1 15.5 -2.93 7.64e+ 0 5.72e- 1 -0.806
## 6 A06 G1 12.6 -5.77 5.44e+ 1 4.07e+ 0 2.03
## 7 A01 G2 12.7 -5.71 5.22e+ 1 3.91e+ 0 1.97
## 8 A02 G2 16.3 -2.09 4.26e+ 0 3.19e- 1 -1.65
## 9 A03 G2 13.1 -5.31 3.96e+ 1 2.97e+ 0 1.57
## 10 Profesor G1 20.0 1.64 3.20e- 1 2.39e- 2 -5.38
## 11 Profesor G2 20.0 1.64 3.20e- 1 2.39e- 2 -5.38
Grafica_comparativa <- ggplot(Dos_DDCt,
aes(x = Well,
y = DosDDCt,
fill = Grupo)) +
geom_col() +
theme_classic() +
labs(title = "Análisis relativo RT-qPCR",
subtitle = "Equipo: LSD",
caption = "Diseño: SZV",
x = "Muestra",
y = "Fold Change (2^-ΔΔCt)")
Grafica_comparativa
Dos_DDCt2 <- Dos_DCt %>%
mutate(
DosDDCt = DosDCt / Control,
L2 = log2(DosDDCt)
)
Grafica_comparativa2 <- ggplot(Dos_DDCt2,
aes(x = Well,
y = L2,
fill = Grupo)) +
geom_col() +
theme_classic() +
labs(title = "Análisis relativo RT-qPCR",
subtitle = "Equipo: LSD",
caption = "Diseño: SZV",
x = "Muestra",
y = "Log2(Fold Change)") +
geom_hline(yintercept = 0,
linetype = "solid",
color = "black",
linewidth = 0.2)
Grafica_comparativa2
