bioRxivBioinformaticsPreprint
Multi-condition and multi-modal temporal profile inference during mouse embryonic development
Ran ZhangiD, Chengxiang QiuiD, Galina N. Filippova, Gang LiiD, Jay ShendureiD, Jean‐Philippe VertiD, Xinxian DengiD, Christine M. DistècheiD, William Stafford NobleiD
Abstract
The emergence of single-cell time-series datasets enables modeling of changes in various types of cellular profiles over time. However, due to the disruptive nature of single-cell measurements, it is impossible to capture the full temporal trajectory of a particular cell. Furthermore, single-cell profiles can be collected at mismatched time points across different conditions (e.g., sex, batch, disease) and data modalities (e.g., scRNA-seq, scATAC-seq), which makes modeling challenging. Here we propose a joint modeling framework, Sunbear, for integrating multi-condition and multi-modal single-cell profiles across time. Sunbear can be used to impute single-cell temporal profile changes, align multi-dataset and multi-modal profiles across time, and extrapolate single-cell profiles in a missing modality. We applied Sunbear to reveal sex-biased transcription during mouse embryonic development and predict dynamic relationships between epigenetic priming and transcription for cells in which multi-modal profiles are unavailable. Sunbear thus enables the projection of single-cell time-series snapshots to multi-modal and multi-condition views of cellular trajectories.
- organism: mouse
- assay: scRNA-seq
- assay: scATAC-seq
- research focus: trajectory inference
- research focus: dimensionality reduction
- research focus: imputation
- approach: statistical model
- Citations
- 3
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