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scDALI: modeling allelic heterogeneity in single cells reveals context-specific genetic regulation

While it is established that the functional impact of genetic variation can vary across cell types and states, capturing this diversity remains challenging. Current studies using bulk sequencing either ignore this heterogeneity or use sorted cell populations, reducing discovery and explanatory power...

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Detalles Bibliográficos
Autores principales: Heinen, Tobias, Secchia, Stefano, Reddington, James P., Zhao, Bingqing, Furlong, Eileen E. M., Stegle, Oliver
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8734213/
https://www.ncbi.nlm.nih.gov/pubmed/34991671
http://dx.doi.org/10.1186/s13059-021-02593-8
Descripción
Sumario:While it is established that the functional impact of genetic variation can vary across cell types and states, capturing this diversity remains challenging. Current studies using bulk sequencing either ignore this heterogeneity or use sorted cell populations, reducing discovery and explanatory power. Here, we develop scDALI, a versatile computational framework that integrates information on cellular states with allelic quantifications of single-cell sequencing data to characterize cell-state-specific genetic effects. We apply scDALI to scATAC-seq profiles from developing F1 Drosophila embryos and scRNA-seq from differentiating human iPSCs, uncovering heterogeneous genetic effects in specific lineages, developmental stages, or cell types. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02593-8.