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Multi-condition and multi-modal temporal profile inference during mouse embryonic development.
Zhang, Ran; Qiu, Chengxiang; Filippova, Gala; Li, Gang; Shendure, Jay; Vert, Jean-Philippe; Deng, Xinxian; Disteche, Christine; Noble, William Stafford.
Afiliação
  • Zhang R; Department of Genome Sciences, University of Washington.
  • Qiu C; eScience Institute, University of Washington.
  • Filippova G; Department of Genome Sciences, University of Washington.
  • Li G; Department of Pathology, University of Washington.
  • Shendure J; Department of Genome Sciences, University of Washington.
  • Vert JP; eScience Institute, University of Washington.
  • Deng X; Brotman Baty Institute for Precision Medicine, University of Washington.
  • Disteche C; Howard Hughes Medical Institute.
  • Noble WS; Allen Center for Cell Lineage Tracing.
bioRxiv ; 2024 Mar 04.
Article em En | MEDLINE | ID: mdl-38496477
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.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: BioRxiv Ano de publicação: 2024 Tipo de documento: Article País de publicação: EEUU / ESTADOS UNIDOS / ESTADOS UNIDOS DA AMERICA / EUA / UNITED STATES / UNITED STATES OF AMERICA / US / USA

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: BioRxiv Ano de publicação: 2024 Tipo de documento: Article País de publicação: EEUU / ESTADOS UNIDOS / ESTADOS UNIDOS DA AMERICA / EUA / UNITED STATES / UNITED STATES OF AMERICA / US / USA