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

ABSTRACT: A common approach to benchmarking of single-cell transcriptomics tools is to generate synthetic datasets that statistically resemble experimental data. However, most existing single-cell simulators do not incorporate transcription factor-gene regulatory interactions that underlie expression dynamics. Here, we present SERGIO, a simulator of single-cell gene expression data that models the stochastic nature of transcription as well as regulation of genes by multiple transcription factors according to a user-provided gene regulatory network. SERGIO can simulate any number of cell types in steady state or cells differentiating to multiple fates. We show that datasets generated by SERGIO are statistically comparable to experimental data generated by Illumina HiSeq2000, Drop-seq, Illumina 10X ch

SUBMITTER: Dibaeinia P 

PROVIDER: S-EPMC7530147 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature