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

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 efficie...

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Detalles Bibliográficos
Autores principales: You, Yupei, Prawer, Yair D. J., De Paoli-Iseppi, Ricardo, Hunt, Cameron P. J., Parish, Clare L., Shim, Heejung, Clark, Michael B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10077662/
https://www.ncbi.nlm.nih.gov/pubmed/37024980
http://dx.doi.org/10.1186/s13059-023-02907-y
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-02907-y.