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

Genome Biol. 2023 Apr 6;24(1):66. doi: 10.1186/s13059-023-02907-y.

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 .

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Gene Expression Profiling / methods
  • RNA Isoforms*
  • Sequence Analysis, RNA / methods
  • Single-Cell Analysis / methods
  • Single-Cell Gene Expression Analysis*
  • Software

Substances

  • RNA Isoforms