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Automatic quality control of single-cell and single-nucleus RNA-seq using valiDrops.

Gabija Kavaliauskaite1,2, Jesper Grud Skat Madsen2,3,4

  • 1Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense M 5230, Denmark.

NAR Genomics and Bioinformatics
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Summary

valiDrops is a new automated method that improves single-cell RNA sequencing (scRNA-seq) data quality by identifying high-quality cells and flagging dead cells for better biological interpretation.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Single-cell and single-nucleus RNA sequencing (scRNA-seq) are powerful tools for cell type and state characterization.
  • RNA contamination from damaged cells during scRNA-seq can distort biological signals.
  • Identifying high-quality cells is crucial for accurate scRNA-seq data analysis.

Purpose of the Study:

  • To introduce valiDrops, an automated method for identifying high-quality barcodes and flagging dead cells in scRNA-seq data.
  • To enhance the biological interpretability of scRNA-seq datasets.

Main Methods:

  • valiDrops employs data-adaptive thresholding on standard quality metrics for initial barcode filtering.
  • A novel clustering-based approach is used to identify barcodes with distinct biological signals.
  • The method was benchmarked against existing tools for scRNA-seq data processing.

Main Results:

  • Filtering with valiDrops resulted in more distinct, separable, and consistent biological signals from cell types and states.
  • valiDrops accurately predicts and flags dead cells.
  • The method is available as an open-source R package.

Conclusions:

  • valiDrops is an effective and user-friendly method for improving scRNA-seq data quality.
  • The tool enhances biological interpretation by providing cleaner datasets and enabling dead cell analysis.
  • This method offers significant advantages over existing tools for scRNA-seq data processing.