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splatPop: simulating population scale single-cell RNA sequencing data.

Christina B AzodiLuke ZappiaAlicia OshlackDavis J McCarthy
Published in: Genome biology (2021)
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.
Keyphrases
  • single cell
  • rna seq
  • high throughput
  • genome wide
  • poor prognosis
  • electronic health record
  • big data
  • binding protein
  • stem cells
  • dna methylation
  • long non coding rna
  • bone marrow
  • solid state