Cuantificación Absoluta
Paulo, Danna, Alegría, Neto
2025-05-05
if(!require("pacman"))
install.packages("pacman")## Cargando paquete requerido: pacmanlibrary("pacman")p_load("vroom",
"ggplot2",
"dplyr",
"ggrepel",
"tidyverse",
"scales")Datos_PCR <- vroom("https://raw.githubusercontent.com/ManuelLaraMVZ/resultados_PCR_practica/refs/heads/main/Cts1.csv")## Rows: 32 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: 32 × 5
## Well Grupo Practica Fluor Cq
## <chr> <chr> <chr> <chr> <dbl>
## 1 A01 G1 Relativa SYBR 30.8
## 2 B01 G1 Relativa SYBR 41
## 3 C01 G1 Relativa SYBR 26.1
## 4 D01 G1 Relativa SYBR 41
## 5 E01 G1 Relativa SYBR 41
## 6 F01 G1 Relativa SYBR 22.3
## 7 Profesor G1 Relativa SYBR 30.7
## 8 Profesor G2 Relativa SYBR 30.7
## 9 B01 G2 Relativa SYBR 20.3
## 10 C01 G2 Relativa SYBR 18.7
## # ℹ 22 more rowsDatos_curva <- Datos_PCR %>%
filter(Practica=="Absoluta",
Grupo== "Curva") %>%
select("Well","Cq") %>%
mutate(Well=as.numeric(Well),
Curva= Well,
LogConc= log10(Curva)) %>%
select(3,4,2)
Datos_curva## # A tibble: 7 × 3
## Curva LogConc Cq
## <dbl> <dbl> <dbl>
## 1 1000 3 12.4
## 2 100 2 15.6
## 3 10 1 18.8
## 4 1 0 22
## 5 0.1 -1 25.2
## 6 0.01 -2 28.4
## 7 0.001 -3 34.8Grafica <- ggplot(Datos_curva,
aes(x=LogConc,
y=Cq))+
geom_point(color="#900C3F",size=4)+
theme_classic()
Grafica
Ajuste lineal
modelo_lineal <- lm(data=Datos_curva, Cq ~ LogConc)
modelo_lineal##
## Call:
## lm(formula = Cq ~ LogConc, data = Datos_curva)
##
## Coefficients:
## (Intercept) LogConc
## 22.457 -3.543Obtencion de coeficientes
coeficientes <- coef(modelo_lineal)
coeficientes## (Intercept) LogConc
## 22.457143 -3.542857Pendiente
pendiente <- round(coeficientes[2],2)
pendiente## LogConc
## -3.54y0 <- round(coeficientes[1],2)
y0## (Intercept)
## 22.46Predicción modelo
prediccion <- data.frame(LogConc= seq(min(Datos_curva$LogConc),
max(Datos_curva$LogConc),
length.out=100))
prediccion$Cq <- predict(modelo_lineal, newdata = prediccion)
head(prediccion)## LogConc Cq
## 1 -3.000000 33.08571
## 2 -2.939394 32.87100
## 3 -2.878788 32.65628
## 4 -2.818182 32.44156
## 5 -2.757576 32.22684
## 6 -2.696970 32.01212R2
resumen_modelo <- summary(modelo_lineal)
resumen_modelo##
## Call:
## lm(formula = Cq ~ LogConc, data = Datos_curva)
##
## Residuals:
## 1 2 3 4 5 6 7
## 0.5714 0.2286 -0.1143 -0.4571 -0.8000 -1.1429 1.7143
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 22.4571 0.3959 56.73 3.22e-08 ***
## LogConc -3.5429 0.1979 -17.90 1.00e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.047 on 5 degrees of freedom
## Multiple R-squared: 0.9846, Adjusted R-squared: 0.9816
## F-statistic: 320.3 on 1 and 5 DF, p-value: 9.997e-06R2 <- round(resumen_modelo$r.squared,4)
R2## [1] 0.9846Ecuación de la recta
ecuacion_recta <-paste0("y=", pendiente,"x+",y0,"\nR2 =",R2)
cat("y=", pendiente,"x+",y0,"\nR2 =",R2)## y= -3.54 x+ 22.46
## R2 = 0.9846Gráfica del ajuste y de la ecuación
Grafica_ajuste <- Grafica+
geom_smooth(data = prediccion,
aes(x= LogConc,
y=Cq),
color="#FFC3DF",
size=1.5)+
labs(title = "Curva estándar de RT-PCR y [Plásmido]",
subtitle = "NADP",
caption= "Diseñó NADP",
x="Log10 (Concentración) [pg/uL]",
y="Cycle threshold (CT)")+
theme_classic(base_size = 15)+
scale_y_continuous(labels = number_format(accuracy = 1))+
theme(plot.title = element_text(hjust = 0.5, face = "bold"),
axis.title.x=element_text(face ="bold"),
axis.title.y=element_text(face ="bold"))+
annotate("text",
x=max(Datos_curva$LogConc)-1.5,
y=min(Datos_curva$Cq)+13,
label=ecuacion_recta,
color="#382",
size=5,
fontface= "bold",
hjust=0)## 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.Grafica_ajuste## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
Predicción de la concentración de la muestra
Datos_muestra <- Datos_PCR %>%
filter(Practica=="Absoluta",
Grupo=="G2",
Well=="A05") %>%
select("Well","Cq")
Datos_muestra## # A tibble: 1 × 2
## Well Cq
## <chr> <dbl>
## 1 A05 18.6Obtener el valor de CT
Ct_muestra <- round(Datos_muestra$Cq,2)
Ct_muestra## [1] 18.64Obtener el valor de X (logconc)
LogConc_calculado <- (Ct_muestra-y0)/pendiente
LogConc_calculado## (Intercept)
## 1.079096Valor Real de conc
Valor_real <- 10^LogConc_calculado
cat("La concentración de la muestra es :",round(Valor_real,2),"pg/uL")## La concentración de la muestra es : 12 pg/uLConstrucciópn del dataframe de la muestra
Datos_muestra_nuestra <- data.frame(Concentracion_real=round(Valor_real,2),
LogConc=round(LogConc_calculado,2),
Cq=Ct_muestra)
Datos_muestra_nuestra## Concentracion_real LogConc Cq
## (Intercept) 12 1.08 18.64Gráfica de la muestra
Grafica_muestra <- Grafica_ajuste+
geom_point(data = Datos_muestra_nuestra,
aes(x=LogConc,
y=Cq),
color= "black",
size=6,
shape=20)+
geom_segment(aes(x=min(Datos_curva$LogConc), xend = LogConc_calculado,
y= Ct_muestra, yend=Ct_muestra),
linetype="dotted",
color="#2f2d2c",
size=1.5)+
geom_segment(aes(x=LogConc_calculado,xend = LogConc_calculado,
y= min(Datos_curva$Cq),yend = Ct_muestra),
linetype="dotted",
color="#2f2d2c",
size=1.5)+
annotate("text",
x=LogConc_calculado,
y=Ct_muestra,
label=paste0("[Plásmido]=",round(Valor_real,2),"pg/uL"),
color="black",
fontface ="bold",
hjust=-0.007,
vjust=-10)
Grafica_muestra## Warning: Use of `Datos_curva$LogConc` is discouraged.
## ℹ Use `LogConc` instead.## Warning in geom_segment(aes(x = min(Datos_curva$LogConc), xend = LogConc_calculado, : All aesthetics have length 1, but the data has 7 rows.
## ℹ Please consider using `annotate()` or provide this layer with data containing
## a single row.## Warning: Use of `Datos_curva$Cq` is discouraged.
## ℹ Use `Cq` instead.## Warning in geom_segment(aes(x = LogConc_calculado, xend = LogConc_calculado, : All aesthetics have length 1, but the data has 7 rows.
## ℹ Please consider using `annotate()` or provide this layer with data containing
## a single row.## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'