splatPop: simulating population scale single-cell RNA sequencing data
- Author(s)
- Azodi, CB; Zappia, L; Oshlack, A; McCarthy, DJ;
- Journal Title
- Genome Biology
- Publication Type
- Protocol
- Abstract
- 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.
- Keywords
- Benchmarking; Cluster Analysis; Computer Simulation; Gene Expression Profiling/methods; Genomics; Humans; Quantitative Trait Loci; Sequence Analysis, RNA/*methods; Single-Cell Analysis/*methods; Software
- Department(s)
- Laboratory Research
- PubMed ID
- 34911537
- Publisher's Version
- https://doi.org/10.1186/s13059-021-02546-1
- Open Access at Publisher's Site
https://doi.org/10.1186/s13059-021-02546-1- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2025-05-23 08:13:59
Last Modified: 2025-05-23 08:15:07