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Plot group comparison bar chart

plot_compare.Rd

Generate grouped bar plots with error bars for comparing connectivity metrics between groups.

Usage

plot_compare(
  data,
  conn_vars,
  group,
  error_bar = c("se", "sd", "ci", "none"),
  show_zero = TRUE,
  clean_labels = TRUE,
  title = NULL
)

Arguments

data

Data frame with one row per subject containing connectivity values and a grouping column

conn_vars

Character vector of column names in data to compare. Each becomes a category on the x-axis

group

Character string naming the grouping column in data. Must be a factor or character column with 2 or more levels

error_bar

Character. Type of error bar to display. One of:

  • "se" (default): standard error of the mean

  • "sd": standard deviation

  • "ci": 95 percent confidence interval

  • "none": no error bars

show_zero

Logical. If TRUE (default), draw a dotted horizontal reference line at y = 0

clean_labels

Logical. If TRUE (default), clean column names for x-axis display by replacing underscores with hyphens and applying title case. If FALSE, use raw column names

title

Optional character string for the plot title

Value

A ggplot object that can be further customized with standard ggplot2 syntax.

Details

The function computes per-group summary statistics (mean and error bars) from the input data frame, then generates a grouped bar plot with one cluster per connectivity variable.

The function works with any column names, not limited to calc_* output. Any numeric columns in the data frame can be used as conn_vars.

X-axis labels can always be overridden with + scale_x_discrete(labels = ...) regardless of the clean_labels setting.

See also

plot_heatmap for connectivity matrix heatmaps. plot_scatter for connectivity-behavior scatter plots. calc_within, calc_between, calc_conn for generating connectivity data.

Examples

# Within-network comparison by group
indices <- get_indices(ex_conn_array, roi_include = "schaefer")
within_df <- calc_within(ex_conn_array, indices)
within_df$group <- rep(c("YA", "OA"), times = c(5, 5))

plot_compare(within_df,
  conn_vars = c("within_default", "within_vis"),
  group = "group"
)


# ROI-to-network comparison
indices_all <- get_indices(ex_conn_array)
ahip_df <- calc_conn(ex_conn_array, indices_all,
  from = "ahip", to = c("default", "cont", "vis")
)
ahip_df$group <- rep(c("YA", "OA"), times = c(5, 5))

plot_compare(ahip_df,
  conn_vars = c("ahip_default", "ahip_cont", "ahip_vis"),
  group = "group"
)


# Custom labels override clean_labels
plot_compare(within_df,
  conn_vars = c("within_default", "within_vis"),
  group = "group"
) + ggplot2::scale_x_discrete(labels = c("DMN", "VIS"))
#> Scale for x is already present.
#> Adding another scale for x, which will replace the existing scale.


if (FALSE) { # \dontrun{
# Full workflow with real data
z_mat <- load_matrices("data/conn.mat", type = "zmat", exclude = c(3, 5))
indices <- get_indices(z_mat, roi_include = "schaefer")
within_df <- calc_within(z_mat, indices)
within_df$group <- demo$group

plot_compare(within_df,
  conn_vars = c("within_default", "within_cont", "within_vis"),
  group = "group",
  title = "Within-Network Connectivity by Age Group"
)
} # }