Known limitations

mantispy is in alpha. These are the gaps to know about before you build on it.

• Case studies are not re-executed in CI. The tutorials run on every change, but the case-study notebooks ship with stored outputs and are only re-run by hand, so their outputs can lag behind the code.

• One perturbation per object, by design. Each row is a member of a single perturbation. A cell carrying more than one guide is a QC artifact that is expected to be filtered out upstream, in your own pipeline, before stamping, so multi-membership is out of scope rather than unimplemented. In pooled screens the guide is the perturbation identity (recorded in uns["mantispy"]["perturbation"]) and is aggregated to genes downstream; see Genetic screens.

• Performance is not tuned for full JUMP scale. The functions are correct on large screens, but some use memory or time that grows quickly with the number of profiles.

• SpatialData is read-only. Images and segmentations are read through io.read_plate, and nothing is written back to the SpatialData object.