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library(tidyverse)
library(ggpubr)
data <- read_csv("../csv/data_per_assay_per_year_per_outcome.csv")
tbl <- data %>%
mutate(
assay_type = factor(assay, labels = (
c(
"MSD (Arb. Intensity)",
"Multiplex cytokine (log2 Z-score)",
"Cell Cytometry (% parent popul.)",
"Multiplex cytokine (log2 Z-score)",
"Phospho cytometry (flow cytometery,\n 90 %tile fold-change)",
"Cell Cytometry (% parent popul.)",
"Phospho cytometry (Mass cytometry, arcsinh diff.)",
"Complete blood count (abs. count/uL)",
"MSD (Arb. Intensity)",
"Cell Cytometry (% parent popul.)",
"MSD (Arb. Intensity)",
"Multiplex cytokine (log2 Z-score)",
"Multiplex cytokine (log2 Z-score)",
"Cell Cytometry (% parent popul.)"
)
))
) %>%
filter(
!(assay_type=="Phospho cytometry (flow cytometery,\n 90 %tile fold-change)"
&
data > 10000)
)
plt <- tbl %>%
ggplot(aes(data, fill=assay_type)) +
geom_histogram(show.legend=F) +
facet_wrap(~ factor(assay_type), scales="free") +
theme_pubclean()
plt
ggsave("../images/assay_value_distributions.png", plt, width = 2 * 15, height = 19, units = "cm")
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