Ontology highlight
ABSTRACT:
SUBMITTER: Kana O
PROVIDER: S-EPMC10436058 | biostudies-literature | 2023 Aug
REPOSITORIES: biostudies-literature
Kana Omar O Nault Rance R Filipovic David D Marri Daniel D Zacharewski Tim T Bhattacharya Sudin S
Patterns (New York, N.Y.) 20230811 8
Single-cell sequencing reveals the heterogeneity of cellular response to chemical perturbations. However, testing all relevant combinations of cell types, chemicals, and doses is a daunting task. A deep generative learning formalism called variational autoencoders (VAEs) has been effective in predicting single-cell gene expression perturbations for single doses. Here, we introduce single-cell variational inference of dose-response (scVIDR), a VAE-based model that predicts both single-dose and mu ...[more]