Question 1

How do I install Pycytominer using pip?

Accepted Answer

Run 'pip install pycytominer' for the base package. For additional features like collate or cell locations, use extras like 'pip install pycytominer[collate]', as detailed in the Installation section.

Question 2

Pycytominer vs CytoTable: what's the difference?

Accepted Answer

Pycytominer processes and normalizes feature profiles for analysis, while CytoTable converts and harmonizes raw image analysis outputs into a format ready for Pycytominer. They are complementary tools in the cytomining ecosystem.

Question 3

How to normalize data with Pycytominer in Python?

Accepted Answer

Call pycytominer.normalize() with profiles as a DataFrame, specify a method like 'standardize', and use the samples parameter for control groups, as shown in the Usage example with real-world data from CellProfiler.

Question 4

Does Pycytominer work with deep learning-based feature extraction?

Accepted Answer

Yes, it supports DeepProfiler outputs through pycytominer.cyto_utils, but may require additional steps for data preparation compared to CellProfiler, and integration is less seamless out-of-the-box.

Question 5

What should I do if Pycytominer runs out of memory?

Accepted Answer

For large SQLite files, consider using CytoTable to convert to parquet format or process in chunks, as the README notes resource limitations and recommends this for better performance.

Question 6

Can I use Pycytominer with In Carta software?

Accepted Answer

Yes, but you need to pre-harmonize data using CytoTable, as recommended in the Handling inputs section, and manually specify features in functions like normalize to avoid issues.

Pycytominer

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