#' plot cell count by batch variables as a scatter plot
#'
#'@param well_scores tibble::tibble as output by read_well_scores
#'@param subtitle plot subtitle, typically the study identifier
#'@return ggplot2 object with the lattice plot with a panel for each batch variable
#'
#'@export
plot_score_by_batch_vars_scatter <- function(well_scores, subtitle=NULL){
data <- well_scores %>%
dplyr::filter(!is_control) %>%
dplyr::select(
week, plate, row, # batch variables
prob_positive)%>% # response values
tidyr::pivot_longer(
cols=c("week", "plate", "row"),
names_to="batch_variable",
values_to="batch_value")
p <- ggplot2::ggplot(data=data) +
ggplot2::theme_bw() +
ggplot2::geom_jitter(
mapping=ggplot2::aes(
x=batch_value,
y=prob_positive),
size=.8,
height=0,
width=.2) +
ggplot2::geom_smooth(
mapping=ggplot2::aes(
x=batch_value,
y=prob_positive),
method="lm") +
ggplot2::facet_wrap(
facets=ggplot2::vars(batch_variable),
scales="free_x") +
ggplot2::scale_x_continuous(
"Batch Value") +
ggplot2::scale_y_continuous(
"Score",
limits=c(0,1),
labels=scales::percent_format()) +
ggplot2::ggtitle(
label="Classifier Score by Batch Dimensions",
subtitle=subtitle)
}
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