Instalar y correr paqueteria

install.packages("pacman")
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.4'
## (as 'lib' is unspecified)
library("pacman")

p_load("readr","dplyr","ggplot2")
PCR <- read.csv(file="https://raw.githubusercontent.com/ManuelLaraMVZ/Transcript-mica/main/datos_miRNAs.csv")

PCR

Asilar el control y seleccionar solo a U6

Gen_ref <- PCR %>% 
  filter(Condicion=="Control") %>% 
  select(-2) %>% 
  filter(Gen=="U6 snRNA-001973")

Gen_ref
Gen_int <- PCR %>% 
  filter(Condicion=="Target") %>% 
  select(-2)

Gen_int
Mean_ref <- Gen_ref %>% 
  mutate(Prom_Cx=(Cx1+Cx2+Cx3)/3,
         Prom_Tx=(T1+T2+T3)/3) %>% 
  select("Gen","Prom_Cx","Prom_Tx")
Mean_ref
Mean_int <- Gen_int %>% 
  mutate(Prom_Cx=(Cx1+Cx2+Cx3)/3,
         Prom_Tx=(T1+T2+T3)/3) %>% 
  select("Gen","Prom_Cx","Prom_Tx")
Mean_int
Analisis <- Mean_int %>% 
  mutate(DCT_Cx=Mean_int$Prom_Cx-Mean_ref$Prom_Cx,
         DCT_Tx=Mean_int$Prom_Tx-Mean_ref$Prom_Tx,
         DosDCT_Cx=2^-(DCT_Cx),
         DosDCT_Tx=2^-(DCT_Tx)) %>% 
  mutate(DosDDCT=DosDCT_Tx/DosDCT_Cx)
Analisis
Grafica_1 <- ggplot(Analisis,
                    mapping = aes(x=DosDCT_Cx,
                                  y=DosDCT_Tx))+
  geom_point(color="#FF5733")+
  theme_classic()+
  labs(title="cambios de expresión de miRNAs",
       subtitle="Gráfica de dispersión",
       caption="Creo: José Ernesto Arriaza",
       x="Condición control(2^-DCt)",
       y="Tratamiento(2^-DCt)")+
  geom_smooth(method = "lm",
              color="orange",
              alpha=0.005,
              linewidth=0.2)
Grafica_1
## `geom_smooth()` using formula = 'y ~ x'