Genome Biology (Apr 2023)

Identification of cell barcodes from long-read single-cell RNA-seq with BLAZE

  • Yupei You,
  • Yair D. J. Prawer,
  • Ricardo De Paoli-Iseppi,
  • Cameron P. J. Hunt,
  • Clare L. Parish,
  • Heejung Shim,
  • Michael B. Clark

DOI
https://doi.org/10.1186/s13059-023-02907-y
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 23

Abstract

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Abstract Long-read single-cell RNA sequencing (scRNA-seq) enables the quantification of RNA isoforms in individual cells. However, long-read scRNA-seq using the Oxford Nanopore platform has largely relied upon matched short-read data to identify cell barcodes. We introduce BLAZE, which accurately and efficiently identifies 10x cell barcodes using only nanopore long-read scRNA-seq data. BLAZE outperforms the existing tools and provides an accurate representation of the cells present in long-read scRNA-seq when compared to matched short reads. BLAZE simplifies long-read scRNA-seq while improving the results, is compatible with downstream tools accepting a cell barcode file, and is available at https://github.com/shimlab/BLAZE .