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STARsolo: accurate, fast and versatile mapping/quantification of single-cell and single-nucleus RNA-seq data

View ORCID ProfileBenjamin Kaminow, View ORCID ProfileDinar Yunusov, View ORCID ProfileAlexander Dobin
doi: https://doi.org/10.1101/2021.05.05.442755
Benjamin Kaminow
Cold Spring Harbor Laboratory, NY, 11724
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Dinar Yunusov
Cold Spring Harbor Laboratory, NY, 11724
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Alexander Dobin
Cold Spring Harbor Laboratory, NY, 11724
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Abstract

We present STARsolo, a comprehensive turnkey solution for quantifying gene expression in single-cell/nucleus RNA-seq data, built into RNA-seq aligner STAR. Using simulated data that closely resembles realistic scRNA-seq, we demonstrate that STARsolo is highly accurate and significantly outperforms pseudoalignment-to-transcriptome tools. STARsolo can replicate the results of, but is considerably faster than CellRanger, currently the most widely used tool for pre-processing scRNA-seq data. In addition to uniquely mapped reads, STARsolo takes account of multi-gene reads, necessary to detect certain classes of biologically important genes. It has a flexible cell barcode processing scheme, compatible with many established scRNA-seq protocols, and extendable to emerging technologies. STARsolo can quantify transcriptomic features beyond gene expression, which we illustrate by analyzing cell-type-specific alternative splicing in the Tabula Muris project.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted May 05, 2021.
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STARsolo: accurate, fast and versatile mapping/quantification of single-cell and single-nucleus RNA-seq data
Benjamin Kaminow, Dinar Yunusov, Alexander Dobin
bioRxiv 2021.05.05.442755; doi: https://doi.org/10.1101/2021.05.05.442755
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STARsolo: accurate, fast and versatile mapping/quantification of single-cell and single-nucleus RNA-seq data
Benjamin Kaminow, Dinar Yunusov, Alexander Dobin
bioRxiv 2021.05.05.442755; doi: https://doi.org/10.1101/2021.05.05.442755

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