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Palma, A. ; Richter, T. ; Zhang, H. ; Lubetzk, M. ; Tong, A.* ; Dittadi, A. ; Theis, F.J.

Multi-modal and multi-attribute generation of single cells with CFGen.

In: (The Thirteenth International Conference on Learning Representations, ICLR 2025). 2025. accepted
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Generative modeling of single-cell RNA-seq data is crucial for tasks like trajectory inference, batch effect removal, and simulation of realistic cellular data. However, recent deep generative models simulating synthetic single cells from noise operate on pre-processed continuous gene expression approximations, overlooking the discrete nature of single-cell data, which limits their effectiveness and hinders the incorporation of robust noise models. Additionally, aspects like controllable multi- modal and multi-label generation of cellular data remain underexplored. This work introduces CellFlow for Generation (CFGen), a flow-based conditional generative model that preserves the inherent discreteness of single-cell data. CFGen generates whole-genome multi-modal single-cell data reliably, improving the recovery of crucial biological data characteristics while tackling relevant generative tasks such as rare cell type augmentation and batch correction. We also introduce a novel framework for compositional data generation using Flow Matching. By showcasing CFGen on a diverse set of biological datasets and settings, we provide evidence of its value to the fields of computational biology and deep generative models.
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Publikationstyp Artikel: Konferenzbeitrag
Korrespondenzautor
Konferenztitel The Thirteenth International Conference on Learning Representations, ICLR 2025
Nichtpatentliteratur Publikationen
Institut(e) Institute of Computational Biology (ICB)
Helmholtz Artifical Intelligence Cooperation Unit (HAICU)
Copyright Copyright 2025 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.