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astir is a modelling framework for the assignment of cell type and cell state across a range of single-cell technologies such as Imaging Mass Cytometry (IMC). astir is built using pytorch and uses recognition networks for fast minibatch stochastic variational inference.
- Automated assignment of cell type and state from highly multiplexed imaging and proteomic data
- Diagnostic measures to check quality of resulting type and state inferences
- Ability to map new data to cell types and states trained on existing data using recognition neural networks
- A range of plotting and data loading utilities
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