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smartSim: simulation of splice aware single cell smart-seq3 data.

Marie Van Hecke1,2,3, Kathleen Marchal1,2,3

  • 1IDLab, Department of Information Technology, Ghent University-imec, 9052 Ghent, Belgium.

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|August 27, 2025
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Summary
This summary is machine-generated.

smartSim is a new simulator for Smart-seq3 sequencing data, crucial for developing computational tools. It generates realistic data to improve isoform reconstruction and alternative splicing analysis in single-cell RNA sequencing.

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Area of Science:

  • Single-cell RNA sequencing
  • Computational biology
  • Bioinformatics

Background:

  • Smart-seq3 is a key protocol for full-length single-cell RNA sequencing, enabling transcript-level and splicing analysis.
  • Benchmarking computational tools for isoform reconstruction and splicing quantification is hindered by the absence of ground truth datasets.

Purpose of the Study:

  • To develop smartSim, a simulator for generating realistic Smart-seq3 sequencing data.
  • To provide a benchmark dataset for evaluating computational methods in single-cell transcriptomics.

Main Methods:

  • smartSim simulates known and novel splicing events, incorporating UMI information and protocol-specific biases.
  • The simulator generates raw sequencing reads in FASTQ format, compatible with standard alignment tools.
  • Empirical data distributions are leveraged to mimic real Smart-seq3 data characteristics.

Main Results:

  • smartSim-generated data closely mirrors real Smart-seq3 datasets in fragment length, read counts, and quality scores.
  • The simulator accurately reflects complexities in single-cell transcriptomics, including UMI-containing and internal reads.
  • Validation confirms the utility of smartSim for assessing computational tools.

Conclusions:

  • smartSim is a valuable resource for advancing computational methods in single-cell RNA sequencing.
  • The simulator facilitates improved alternative splicing detection and isoform reconstruction.
  • smartSim enhances the evaluation of bioinformatics tools for transcriptomics data analysis.