Should I install PyCytoData?

In case you haven’t heard, PyCytoData provides a unified framework for analyzing CyTOF data in python. The supported workflow includes File IO, preprocessing, and dimension reduction and visualization via CytofDR. While we believe in the future of PyCytoData, we recognize that many people prefer a leaner package without the baggage of an ecosystem. Thus, we kindly made PyCytoData to only those who need it. In this tutorial, we walk you through whether you need to install PyCytoData and help you make the best decisions.

Decision at a Glance

If you need a TLDR, we create a nifty flowchart for you to follow. At each step, ask yourself the question and you will arrive at a conclusion. We want to emphasize that currently only the Cytomulate CLI strictly requires PyCytoData because we don’t want to maintain two branches of the same IO code. For all other workflows, you can judge the necessity of Cytomulate yourself.

A flowchart for installing PyCytoData.

How is PyCytoData optional?

Currently, we need PyCytoData for two functionalities:

  • The Cytomulate CLI

  • Outputting to a PyCytoData object

For the former, we require PyCytoData because we rely on its File IO operations so that we don’t have reinvent a great module. For the latter, users have the option to use the sample_to_pycytodata method or just the regular sample method. In the case that PyCytoData is not installed, user can have NumPy arrays returned instead. As you may see, we do not rely on PyCytoData for the core model and estimation procedures. PyCytoData is rather just a convenience feature for those who need it.

In terms of implementation, we check whether PyCytoData is importable at the beginning. If not, no ImportError is raised until absolutely necessary. This means that unless users explicitly call smaple_to_pycytodata without a proper installation, we do not complain! Of course, this implementation has its downsides: namely, it can surprise those who are not aware of the optional dependency. We will revisit this in the future.

What are added benefits of PyCytoData?

The main reason to use PyCytoData is its convenience. Specifically, it can handle batches, metadata, and working with expression matrices easily. For those who want a wrapper around arrays, we believe that PyCytoData is a good fit. Of course, let’s not forget the File IO capabilities and downstream integration with CytofDR.

On the note of downstream analyses, PyCytoData is being actively developed. So, there will be some neat features coming in the futrue when we add more tools and integrate more libraries.

Should I skip PyCytoData for CytofDR directly?

If you are asking this question, then YES! The CytofDR package provides a more complete set of tools for benchmarking and performing DR in CyTOF. While PyCytoData can have workarounds to allow these functionalities, we recommend using CytofDR directly. However, you are always welcomed to install PyCytoData to manage other aspects of the CyTOF workflow.