Gráfica de dispersión

Instalar y correr la paquetería

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")

Cargar la base de datos

PCR <- read_csv(file = "https://raw.githubusercontent.com/ManuelLaraMVZ/Transcript-mica/main/datos_miRNAs.csv")

## Rows: 363 Columns: 8
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): Gen, Condicion
## dbl (6): Cx1, Cx2, Cx3, T1, T2, T3
## 
## 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.

head(PCR)

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

Genref

Selección de datos

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

Promedios

Meanref <- Genref %>% 
  mutate(Prom_Cx = (Cx1+Cx2+Cx3)/3, 
         Prom_Tx = (T1+T2+T3)/3) %>% 
  select("Gen","Prom_Cx","Prom_Tx")

Meanint <- Genint %>% 
  mutate(Prom_Cx = (Cx1+Cx2+Cx3)/3, 
         Prom_Tx = (T1+T2+T3)/3) %>% 
  select("Gen","Prom_Cx","Prom_Tx")

Análisis de datos

Analisis <- Meanint %>% 
  mutate(DCT_Cx = Meanint$Prom_Cx - Meanref$Prom_Cx, 
         DCT_Tx = Meanint$Prom_Tx - Meanref$Prom_Tx,
         DosDCT_Cx = 2^-(DCT_Cx),
         DosDCT_Tx = 2^-(DCT_Tx)) %>% 
  mutate(DosDDCT = DosDCT_Tx / DosDCT_Cx)

Graficar

Gráfica1 <- ggplot(Analisis,
                   mapping = aes (x = DosDCT_Cx,
                                  y = DosDCT_Tx))+
  geom_point(color = "#663399")+
  theme_bw() +
  labs(title = "Cambios de expresión de miRNAs",
       subtitle = "Gráfica de dispersión", 
       caption = "Creado por: Regina Hernández",
       x = "Condición control (2^-DCT",
       y = "Tratamiento (2^-DCT)") +
  geom_smooth(method = "lm",
              color = "#66CDAA",
              alpha = 0.005,
              linewidth = 0.2)

Gráfica1

## `geom_smooth()` using formula = 'y ~ x'