scReadSim: a single-cell RNA-seq and ATAC-seq read simulator.

Area of Science:

• Computational Biology
• Genomics
• Bioinformatics

Background:

• Accurate benchmarking of single-cell RNA sequencing (scRNA-seq) and single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) computational tools requires realistic simulated sequencing reads.
• Existing read simulators do not adequately mimic real biological data, creating a gap in tool development and validation.

Purpose of the Study:

• To introduce scReadSim, a novel simulator for generating synthetic scRNA-seq and scATAC-seq sequencing reads.
• To provide a tool that mimics real data at both read-sequence and read-count levels, incorporating user-specified ground truths.
• To enable the design of cell-type-specific ground-truth open chromatin regions for scATAC-seq data generation.

Main Methods:

• Development of scReadSim, a simulator capable of generating FASTQ or BAM files for scRNA-seq and scATAC-seq data.
• Incorporation of user-defined ground truths, including unique molecular identifier (UMI) counts for scRNA-seq and open chromatin regions for scATAC-seq.
• Mimicking real data characteristics at sequence and count levels for both data types.

Main Results:

• scReadSim successfully generates synthetic scRNA-seq and scATAC-seq data that mimics real sequencing reads and counts.
• The simulator provides crucial ground truth information, such as UMI counts and open chromatin regions.
• Benchmarking using scReadSim demonstrated that UMI-tools excels in scRNA-seq UMI deduplication, while HMMRATAC and MACS3 show top performance in scATAC-seq peak calling.

Conclusions:

• scReadSim addresses the need for realistic simulators in single-cell genomics, facilitating robust benchmarking of computational tools.
• The tool's ability to generate data with specified ground truths enhances the reliability of scRNA-seq and scATAC-seq analysis pipelines.
• scReadSim is a valuable resource for the computational biology community, improving the evaluation and development of single-cell analysis software.