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_datafunction)- 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
FALSEcombines replicates, but future releases will default toTRUEproviding 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
)
