Disentanglement of single-cell data with biolord

Zoe Piran, Niv Cohen, Yedid Hoshen, Mor Nitzan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Biolord is a deep generative method for disentangling single-cell multi-omic data to known and unknown attributes, including spatial, temporal and disease states, used to reveal the decoupled biological signatures over diverse single-cell modalities and biological systems. By virtually shifting cells across states, biolord generates experimentally inaccessible samples, outperforming state-of-the-art methods in predictions of cellular response to unseen drugs and genetic perturbations. Biolord is available at https://github.com/nitzanlab/biolord .

Original languageAmerican English
JournalNature Biotechnology
Early online date15 Jan 2024
DOIs
StateE-pub ahead of print - 15 Jan 2024

Bibliographical note

Publisher Copyright:
© 2024, The Author(s).

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