SERGIO: A Single-Cell Expression Simulator Guided by Gene Regulatory Networks

Payam Dibaeinia; Saurabh Sinha

doi:10.1016/j.cels.2020.08.003

SERGIO: A Single-Cell Expression Simulator Guided by Gene Regulatory Networks

Research output: Contribution to journal › Article › peer-review

Abstract

We present SERGIO, a software tool that can simulate realistic single-cell transcriptomics datasets based on a user-specified gene regulatory network (GRN). Datasets simulated using SERGIO can be used to benchmark a variety of single-cell analysis tools, especially GRN inference methods.

Original language	English (US)
Pages (from-to)	252-271.e11
Journal	Cell Systems
Volume	11
Issue number	3
DOIs	https://doi.org/10.1016/j.cels.2020.08.003
State	Published - Sep 23 2020

Keywords

RNA velocity
benchmarking single-cell analysis tools
differentiation trajectories
gene regulatory networks
simulations
single-cell RNA-seq

ASJC Scopus subject areas

Pathology and Forensic Medicine
Histology
Cell Biology

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title = "SERGIO: A Single-Cell Expression Simulator Guided by Gene Regulatory Networks",

abstract = "We present SERGIO, a software tool that can simulate realistic single-cell transcriptomics datasets based on a user-specified gene regulatory network (GRN). Datasets simulated using SERGIO can be used to benchmark a variety of single-cell analysis tools, especially GRN inference methods.",

keywords = "RNA velocity, benchmarking single-cell analysis tools, differentiation trajectories, gene regulatory networks, simulations, single-cell RNA-seq",

author = "Payam Dibaeinia and Saurabh Sinha",

note = "Funding Information: This work was supported by the National Institutes of Health (grants R35 GM131819A and R01 GM114341A , to S.S.). ",

year = "2020",

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AU - Sinha, Saurabh

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KW - benchmarking single-cell analysis tools

KW - differentiation trajectories

KW - gene regulatory networks

KW - simulations

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