How to load the AKOYA(CODEX) processor pipeline outputs a csv files for Squidpy?

Hi, I am pretty new to the Squidpy. please excuse me with my naive questions.

I have a codex outputs a CSV files but i am not sure how to load the csv files or which tutorial I should follow .

In surate I can use this code to load

codex.obj <- LoadAkoya(filename = "LN7910_20_008_11022020_reg001_compensated.csv",
    type = "processor", fov = "HBM754.WKLP.262")

codex.obj <- NormalizeData(object = codex.obj, normalization.method = "CLR", margin = 2)
codex.obj <- ScaleData(codex.obj)
VariableFeatures(codex.obj) <- rownames(codex.obj)  # since the panel is small, treat all features as variable.
codex.obj <- RunPCA(object = codex.obj, npcs = 20, verbose = FALSE)
codex.obj <- RunUMAP(object = codex.obj, dims = 1:20, verbose = FALSE)
codex.obj <- FindNeighbors(object = codex.obj, dims = 1:20, verbose = FALSE)
codex.obj <- FindClusters(object = codex.obj, verbose = FALSE, resolution = 0.4, n.start = 1)

Thanks for your helps

Squidpy currently has no reader for Flow Cytometry Standard (fcs) files, which is the output format of CODEX (now PhenoCycler). This functionality will soon be added to Squidpy, see the issue on github here.

Will update you here as well once it has been added.

Thats great . Thank you

Hi @DRSEI, this issue has been solved.

CODEX formatted files can now also be used with Squidpy, by using spatialdata-io, which is now used for readers of spatial-omics technologies.

first install latest development version of spatialdata-io:
pip install git+

then import spatialdata_io and load the data:

import spatialdata_io

sdata = spatialdata_io.codex(path="path/to/directory/")

adata = sdata.table

Note: if you don’t use .fcs files but .csv files, set fcs=False in codex().

@LLehner Thank you. I am going to try out today