Splatter: simulation of single-cell RNA sequencing data
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As single-cell RNA sequencing (scRNA-seq) technologies have rapidly developed, so have analysis methods. Many methods have been tested, developed, and validated using simulated datasets. Unfortunately, current simulations are often poorly documented, their similarity to real data is not demonstrated, or reproducible code is not available. Here, we present the Splatter Bioconductor package for simple, reproducible, and well-documented simulation of scRNA-seq data. Splatter provides an interface to multiple simulation methods including Splat, our own simulation, based on a gamma-Poisson distribution. Splat can simulate single populations of cells, populations with multiple cell types, or differentiation paths.
Citation
@article{zappia2017,
author = {Zappia, Luke and Phipson, Belinda and Oshlack, Alicia},
title = {Splatter: Simulation of Single-Cell {RNA} Sequencing Data},
journal = {Genome Biology},
volume = {18},
number = {1},
pages = {174},
date = {2017-09-01},
url = {https://doi.org/10.1186/s13059-017-1305-0},
doi = {10.1186/s13059-017-1305-0},
issn = {1465-6906, 1474-760X},
langid = {en},
abstract = {As single-cell RNA sequencing (scRNA-seq) technologies
have rapidly developed, so have analysis methods. Many methods have
been tested, developed, and validated using simulated datasets.
Unfortunately, current simulations are often poorly documented,
their similarity to real data is not demonstrated, or reproducible
code is not available. Here, we present the Splatter Bioconductor
package for simple, reproducible, and well-documented simulation of
scRNA-seq data. Splatter provides an interface to multiple
simulation methods including Splat, our own simulation, based on a
gamma-Poisson distribution. Splat can simulate single populations of
cells, populations with multiple cell types, or differentiation
paths.}
}