Jeremie Kalfon 👨💻🧬🤖🚀 @jkobject.com · Nov 19 1 / 2
We propose to use the specificity of scRNAseq data and define a multi task pre-training composed of expression denoising, bottleneck learning and classification. We also propose a new hierarchical classification method to work with the rich hierarchical ontologies used to label cells in cellxgene.
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This allows scPRINT zero-shot abilities -meaning no fine-tuning required- such as artificially increasing the depth of the expression profile of a cell (denoising / zero imputation), predicting the cell type, disease, sequencer, and sex of a cell, as well as creating cell embeddings 💪 .