ecotyper: EcoTyper in Python¶
A Python/AnnData port of EcoTyper, the framework for identifying cell states and multicellular communities (ecotypes) in bulk, single-cell and spatial transcriptomes (Luca, Steen et al., Cell 2021).
The port reproduces the R implementation. On all six README tutorials every discrete output (states, ecotypes, ranks, gene sets) is identical to R’s, and every numeric value agrees to within 8e-11 relative. See Benchmarks for the comparison and timings.
Set up the environment and the R repository’s example data and models.
Recover cell states and ecotypes in an AnnData object in five lines.
Step by step through the six EcoTyper tutorials on the bundled data.
Python vs R: wall time, memory and agreement, as charts.
Credit and license¶
EcoTyper was developed by Bogdan A. Luca, Chloé B. Steen, Aaron M. Newman and colleagues. If you use it, cite:
Luca/Steen et al., Atlas of clinically distinct cell states and ecosystems across human solid tumors, Cell 2021, https://doi.org/10.1016/j.cell.2021.09.014
Steen/Luca et al., The landscape of tumor cell states and ecosystems in diffuse large B cell lymphoma, Cancer Cell 2021, https://doi.org/10.1016/j.ccell.2021.08.011
This port is a derivative of EcoTyper, distributed under the same Stanford non-commercial license: free for non-commercial use only. It is an independent port, not affiliated with or endorsed by the EcoTyper authors. CIBERSORTx is closed source and is not part of the port. Steps that need it take precomputed CIBERSORTx outputs as inputs.