Generate OCR and ECAR plots
Usage
rate_plot(
seahorse_rates,
measure = "OCR",
assay = "MITO",
model = "ols",
error_bar = "ci",
conf_int = 0.95,
group_label = "Experimental group",
linewidth = 2,
sep_reps = FALSE,
ci_method = "Wald"
)
Arguments
- seahorse_rates
data.table Seahorse OCR and ECAR rates (imported using
read_data
function)- measure
Whether to plot
"OCR"
or"ECAR"
- assay
What assay to plot (e.g. "MITO" or "GLYCO")
- model
The model used to estimate mean and confidence intervals:
- error_bar
Whether to plot error bars as standard deviation (
"sd"
) or confidence intervals ("ci"
)- conf_int
The confidence interval percentage. Should be between 0 and 1
- group_label
Label for the experimental group to populate the legend title
- linewidth
Width for the lines, passed to
geom_line()
- sep_reps
Whether to calculate summary statistics on the groups with replicates combined. The current default
FALSE
combines replicates, but future releases will default toTRUE
providing replicate-specific summaries.- ci_method
The method used to compute confidence intervals for the mixed-effects model:
"Wald"
,"profile"
, or"boot"
passed tolme4::confint.merMod()
.
Examples
rep_list <- system.file("extdata", package = "ceas") |>
list.files(pattern = "*.xlsx", full.names = TRUE)
seahorse_rates <- read_data(rep_list, sheet = 2)
rate_plot(
seahorse_rates,
measure = "OCR",
error_bar = "ci",
conf_int = 0.95,
sep_reps = FALSE
)
rate_plot(
seahorse_rates,
measure = "OCR",
error_bar = "ci",
conf_int = 0.95,
sep_reps = TRUE
)