Quality control of single-cell ATAC-seq data without peak calling using Chromap.

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Single-cell Assay for Transposase-Accessible Chromatin sequencing (scATAC-seq) is crucial for understanding cellular heterogeneity.
• Existing analysis methods, such as SnapATAC2, use genome-interval-based features, limiting the application of traditional peak-based quality control (QC) metrics.
• Effective QC is essential for accurate interpretation of scATAC-seq data.

Purpose of the Study:

• To extend the Chromap ultrafast alignment tool for scATAC-seq data.
• To enable direct reporting of peak-based QC metrics without prior peak calling.
• To improve the identification of low-quality cells and enhance downstream analysis.

Main Methods:

• Extension of the Chromap algorithm for scATAC-seq data alignment.
• Development of direct reporting of peak-based QC metrics, including fraction of reads in peaks (FRIP).
• Comparative analysis of Chromap's QC metrics against SnapATAC2's cell filtering capabilities.

Main Results:

• Chromap's QC metrics successfully identify low-quality cells that are missed by genome-interval-based methods like SnapATAC2.
• The integration of Chromap's QC metrics leads to improved downstream analysis results.
• The enhanced Chromap method maintains computational efficiency without sacrificing speed.

Conclusions:

• Chromap's direct peak-based QC reporting offers a valuable enhancement for scATAC-seq data analysis.
• This approach improves cell quality assessment and downstream analysis accuracy.
• Chromap provides an efficient and effective solution for scATAC-seq QC, complementing existing interval-based methods.