Access medians per conditions #6
Description
In case you want to access the exact median expressions per condition (or other stats), we have prepared a script for you. First, download your sce object using the button on the upper right. Then, modify your paths:
path_to_sce <- "~/Downloads/sce.rds"
path_to_output <- "~/Downloads/medians_per_condition.csv"
condition <- "condition"
sample_id <- "sample_id"
Install and load packages
install.packages("data.table")
install.packages("ggplot2")
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SingleCellExperiment")
library(SingleCellExperiment)
library(data.table)
library(ggplot2)
Read in your SCE object
sce <- readRDS(path_to_sce)
Extract the expression data and add metadata information
exprs_dt <- data.table(t(assays(sce)$exprs))
exprs_dt[, (condition) := colData(sce)[, condition]]
exprs_dt[, (sample_id) := colData(sce)[, sample_id]]
# reformat for easier calculation
exprs_dt <- melt(exprs_dt, id.vars = c(condition, sample_id), variable.name = "marker", value.name = "exprs")
Calculate medians per condition
median_dt <- exprs_dt[, median(exprs), by=c(condition, "marker")]
colnames(median_dt) <- c(condition, "marker", "median")
print(median_dt)
# export
fwrite(median_dt, path_to_output)
Sanity check: reproduce boxplot from CYANUS
# calculate medians per condition per sample id
median_per_sample_dt <- exprs_dt[, median(exprs), by=c(condition, sample_id, "marker")]
colnames(median_per_sample_dt) <- c(condition, sample_id, "marker", "median")
ggplot()+
geom_boxplot(data = median_per_sample_dt, aes(x = get(condition), y = median, color = get(condition)))+
geom_point(data = median_dt, aes(x = get(condition), y = median))+
facet_wrap(~marker, scales = "free_y")+
theme_bw()
Attention: the median per marker per condition is not the same as the median over the medians per marker per condition per sample id. This is why the black points do not match the boxplot lines exactly.