PomaBoxplots | R Documentation |
PomaBoxplots
generates boxplots and violin plots for samples and features. This function can be used for data exploration (e.g., comparison between pre and post normalized datasets).
PomaBoxplots(
data,
x = "samples",
violin = FALSE,
feature_name = NULL,
theme_params = list(legend_title = FALSE, axis_x_rotate = TRUE)
)
data |
A |
x |
Character. Options are "samples" (to visualize sample boxplots) and "features" (to visualize feature boxplots). Default is "samples". |
violin |
Logical. Indicates if violin plots should be displayed instead of boxplots. Default is FALSE. |
feature_name |
Character vector. Indicates the feature/s to display. Default is NULL (all features will be displayed). |
theme_params |
List. Indicates |
A ggplot
object.
Pol Castellano-Escuder
data("st000284")
# Sample boxplots
st000284 %>%
PomaNorm() %>%
PomaBoxplots(theme_params = list(axistext = "y"))
# Sample violin plots
st000284 %>%
PomaNorm() %>%
PomaBoxplots(violin = TRUE, theme_params = list(axistext = "y"))
# All feature boxplots
st000284 %>%
PomaNorm() %>%
PomaBoxplots(x = "features", theme_params = list(axis_x_rotate = TRUE))
# Specific feature boxplots
st000284 %>%
PomaNorm() %>%
PomaBoxplots(x = "features",
feature_name = c("ornithine", "orotate"))
# Specific feature violin plots
st000284 %>%
PomaNorm() %>%
PomaBoxplots(x = "features",
violin = TRUE,
feature_name = c("ornithine", "orotate"))
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