arrow
Return

splatPop: simulating population scale single-cell RNA sequencing data

delete2021-12-15
delete6
delete
OA
AI
C
Christina B. Azodi
L
Luke Zappia
A
Alicia Oshlack
D
Davis J. McCarthy *
DOI:10.1186/s13059-021-02546-1delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
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:
Single-cell RNA-sequencing
Simulation
Software
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

G
Genome Biology
IF:
9.4
Papers:
6.4K
Citations:
7.3W

Organization

S
st. vincent's institute of medical research
Scholars:
854
Papers: 709
Citations: 0
T
Technical University of Munich
Scholars:
5.2W
Papers: 3.9W
Citations: 6.2W
U
university of melbourne
Scholars:
5.7W
Papers: 5.4W
Citations: 69
researcher View more organizations