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

Payam Dibaeinia1, Saurabh Sinha2

  • 1Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.

Cell Systems
|September 2, 2020
PubMed
Summary

SERGIO is a new simulator for single-cell gene expression data that models transcription factor-gene regulatory networks. It generates realistic synthetic datasets for benchmarking computational tools and understanding cell differentiation.

Keywords:
RNA velocitybenchmarking single-cell analysis toolsdifferentiation trajectoriesgene regulatory networkssimulationssingle-cell RNA-seq

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Area of Science:

  • Computational Biology
  • Genomics
  • Systems Biology

Background:

  • Benchmarking single-cell transcriptomics tools often relies on synthetic data.
  • Existing simulators lack transcription factor-gene regulatory interactions crucial for expression dynamics.

Purpose of the Study:

  • Introduce SERGIO, a novel simulator for single-cell gene expression data.
  • Incorporate stochastic transcription and gene regulation by transcription factors via user-provided networks.

Main Methods:

  • Modeled stochastic transcription and multi-factor gene regulation.
  • Simulated multiple cell types in steady state or during differentiation.
  • Validated SERGIO against experimental datasets from various platforms (e.g., Drop-seq, 10X Chromium).

Main Results:

  • SERGIO-generated data statistically resemble experimental single-cell RNA-seq data.
  • SERGIO enabled benchmarking of single-cell analysis and GRN inference tools.
  • Identified Tcf7, Gata3, and Bcl11b as key T cell differentiation drivers via in silico knockouts.

Conclusions:

  • SERGIO provides a robust platform for simulating biologically realistic single-cell gene expression data.
  • The simulator aids in evaluating computational tools and exploring gene regulatory mechanisms in cell differentiation.
  • SERGIO facilitates in silico experiments to uncover key regulatory factors in biological processes.