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Hi CYANUS team. We have found a small problem with the analysis, although I have access to select all probes that were included in the experiment in the earlier "Clustering" stages "Features to use for clustering", when we reach the "Differential Marker Expression Analysis" stage I do not have access to all of the probes as "Features to use for differential expression analysis". Please see screen shots for examples: We are missing ~10 probes. Any advice you can offer would be greatly appreciated. Best wishes, Emma

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.

Loading the data failed with the following message:
panel[[panel_cols$channel]] %in% colnames(fs) are not all TRUE

Is there any option as non bioinformatician to extract the panel information from an .fcs file quite easy?
I tried 100 times to manually create an .xls or .csv file and the error code above always appears.

Best
mario

Hi there,

I have uploaded my cvs files, after extrapolation of the CD45 positiv population with Flowjow. In the antibodies panel I have the included to the kit mastermix (Human Maxpar) other few antibodies. When I look at the data in cyanus, it looks like as one of the new marker I added doesn´t have any signal. I see the signal with the same csv file in Flowjow.
Do you know why this is happening?
I am happy to discuss this topic further.
Best wishes,
Gabriella

is it possible to have this with the markers instead of the samples? So markers for each clusters?
I also tried the marker densities section from the 2. Visualize Clustering and it doesn´t work, it appear an error, do you know why?

The following error message occurred when uploading the data:
Loading the data failed with the following message:
Empty keyword name detected!If it is due to the double delimiters in keyword value, please set emptyValue to FALSE and try again!