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splatPop: simulating population scale single-cell RNA sequencing data

Population-scale single-cell RNA sequencing (scRNA-seq) is now viable, enabling finer resolution functional genomics studies and leading to a rush to adapt bulk methods and develop new single-cell-specific methods to perform these studies. Simulations are useful for developing, testing, and benchmar...

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Detalles Bibliográficos
Autores principales: Azodi, Christina B., Zappia, Luke, Oshlack, Alicia, McCarthy, Davis J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672480/
https://www.ncbi.nlm.nih.gov/pubmed/34911537
http://dx.doi.org/10.1186/s13059-021-02546-1
Descripción
Sumario:Population-scale single-cell RNA sequencing (scRNA-seq) is now viable, enabling finer resolution functional genomics studies and leading to a rush to adapt bulk methods and develop new single-cell-specific methods to perform these studies. Simulations are useful for developing, testing, and benchmarking methods but current scRNA-seq simulation frameworks do not simulate population-scale data with genetic effects. Here, we present splatPop, a model for flexible, reproducible, and well-documented simulation of population-scale scRNA-seq data with known expression quantitative trait loci. splatPop can also simulate complex batch, cell group, and conditional effects between individuals from different cohorts as well as genetically-driven co-expression. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-021-02546-1).