mantispy

mantispy brings Cell Painting and other image-based profiling data into the scverse ecosystem, from reading what a pipeline wrote through quality control, normalization and batch correction to evaluating what survived.

import mantispy as mt

cells = mt.io.read_profiles("analysis/", platemap="platemap.csv")  # an ExportToSpreadsheet directory, or profile files
mt.pp.annotate_controls(cells)
mt.pp.image_qc(cells)  # which fields were out of focus
mt.pp.normalize(cells, by="Metadata_Plate", reference="negcon")  # robust MAD against the negative controls
wells = mt.tl.aggregate(cells)  # cells -> wells

mt.pp.feature_select(wells)
mt.tl.hit_calling(wells)  # which perturbations moved
mt.pl.hits(wells)

pp prepares, tl computes, pl plots, metrics evaluates a correction, io reads and writes, and ds downloads public screens. Everything operates on an AnnData, so scanpy's PCA, neighbors, UMAP and Leiden work on the same object. io.read_plate reads the images behind the profiles as SpatialData.

To start, From CellProfiler to AnnData shows how to read a screen and Hits and effects how to call hits on it. Neither needs your own data, and mt.ds.bbbc021() downloads a public screen.

Set mt.settings.verbosity = 2 when you first run your own screen. Several steps drop features or wells, and they log it at that level.

Getting started

Please refer to the documentation, in particular, the API documentation.

Installation

You need to have Python 3.12 or newer installed on your system. If you don't have Python installed, we recommend installing uv.

We recommend managing dependencies in project-specific virtual environments to avoid dependency conflicts. This is most convenient using package managers such as uv. Choose from the options below to install mantispy:

1. Install the latest development version:

   pip install git+https://github.com/scverse/mantispy.git  # (or `uv add`)

Reading images needs the spatial extra:

pip install 'mantispy[spatial]'

Release notes

See the changelog.

Contact

For questions and help requests, you can reach out in the scverse discourse. If you found a bug, please use the issue tracker.

Citation

A preprint describing mantispy is in preparation. Until then, cite the repository directly.