Illumina Andrea

1 Community 1

1.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

1.2 NS

lista_NS <- c(orden_deseado, NS)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

1.3 I1

lista_I1 <- c(orden_deseado, I1_5, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

1.4 I2

lista_I2 <- c(orden_deseado, I2_5, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

1.5 I3

lista_I3 <- c(orden_deseado, I3_5, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

1.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

1.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

2 Community 2

2.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

2.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

2.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

2.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

2.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

2.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

2.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

3 Community 3

3.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

3.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

3.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

3.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

3.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

3.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

3.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

4 Community 4

4.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

4.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

4.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

4.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

4.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

4.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

4.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

5 Community 5

5.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

5.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

5.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

5.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

5.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

5.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

5.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

6 Community 6

6.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

6.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

6.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

6.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

6.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

6.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

6.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

7 Community 7

7.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

7.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

7.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

7.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

7.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

7.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

7.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

8 Community 8

8.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

8.2 NS

lista_NS <- c(orden_deseado, NS)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

8.3 I1

lista_I1 <- c(orden_deseado, I1_5, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

8.4 I2

lista_I2 <- c(orden_deseado, I2_5, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

8.5 I3

lista_I3 <- c(orden_deseado, I3_5, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

8.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

8.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

9 Community 9

9.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

9.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

9.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

9.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

9.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

9.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

9.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

10 Community 10

10.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

10.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

10.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

10.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

10.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

10.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

10.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

11 Community 11

11.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

11.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

11.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

11.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

11.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

11.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

11.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

12 Community 12

12.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

12.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

12.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

12.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

12.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

12.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

12.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

13 Community 13

13.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

13.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

13.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

13.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

13.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

13.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

13.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

14 Community 14

14.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

14.2 NS

lista_NS <- c(orden_deseado, NS)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

14.3 I1

lista_I1 <- c(orden_deseado, I1_5, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

14.4 I2

lista_I2 <- c(orden_deseado, I2_5, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

14.5 I3

lista_I3 <- c(orden_deseado, I3_5, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

14.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

14.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

15 Community 15

15.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

15.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

15.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

15.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

15.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

15.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

15.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

16 Community 16

16.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

16.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

16.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

16.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

16.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

16.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

16.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

17 Community 17

17.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

17.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

17.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

17.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

17.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

17.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

17.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

18 Community 18

18.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

18.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

18.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

18.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

18.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

18.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

18.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

19 Community 19

19.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

19.2 NS

lista_NS <- c(orden_deseado, NS)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

19.3 I1

lista_I1 <- c(orden_deseado, I1_5, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

19.4 I2

lista_I2 <- c(orden_deseado, I2_5, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

19.5 I3

lista_I3 <- c(orden_deseado, I3_5, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

19.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

19.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

20 Community 20

20.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

20.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

20.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

20.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

20.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

20.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

20.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

21 Community 21

21.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

21.2 NS

lista_NS <- c(orden_deseado, NS)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

21.3 I1

lista_I1 <- c(orden_deseado, I1_5, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

21.4 I2

lista_I2 <- c(orden_deseado, I2_5, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

21.5 I3

lista_I3 <- c(orden_deseado, I3_5, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

21.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

21.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

22 Community 22

22.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

22.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

22.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

22.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

22.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

22.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

22.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

23 Community 23

23.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

23.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

23.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

23.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

23.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

23.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

23.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

24 Community 24

24.1 Stabilization

df_plot <- df_filtered %>%
  filter(Sample %in% orden_deseado)

ggplot(df_plot, aes(x = factor(Sample, levels = orden_deseado), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

24.2 NS

lista_NS <- c(orden_deseado, NS)
df_plot <- df_filtered %>%
  filter(Sample %in% lista_NS)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_NS), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

24.3 I1

lista_I1 <- c(orden_deseado, I1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

24.4 I2

lista_I2 <- c(orden_deseado, I2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

24.5 I3

lista_I3 <- c(orden_deseado, I3_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_I3)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_I3), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

24.6 M1

lista_M1 <- c(orden_deseado, M1_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M1)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M1), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )

24.7 M2

lista_M2 <- c(orden_deseado, M2_6)

df_plot <- df_filtered %>%
  filter(Sample %in% lista_M2)

ggplot(df_plot, aes(x = factor(Sample, levels = lista_M2), y = Count, fill = taxon)) +
  geom_col(position = "fill") +
  scale_y_continuous(labels = percent_format()) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)
  ) +
  labs(
    x    = "Muestra",
    y    = "Porcentaje de lecturas",
    fill = "Taxon (nivel_valor)"
  )