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Efficient pre-processing of Single-cell ATAC-seq data

View ORCID ProfileFan Gao, View ORCID ProfileLior Pachter
doi: https://doi.org/10.1101/2021.12.08.471788
Fan Gao
1Division of Biology and Biological Engineering; California Institute of Technology, Pasadena, CA, USA
2Caltech Bioinformatics Resource Center; California Institute of Technology, Pasadena, CA, USA
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Lior Pachter
1Division of Biology and Biological Engineering; California Institute of Technology, Pasadena, CA, USA
3Department of Computing & Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA
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  • For correspondence: lpachter@caltech.edu
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ABSTRACT

The primary tool currently used to pre-process 10X Chromium single-cell ATAC-seq data is Cell Ranger, which can take very long to run on standard datasets. To facilitate rapid pre-processing that enables reproducible workflows, we present a suite of tools called scATAK for pre-processing single-cell ATAC-seq data that is 18 times faster than Cell Ranger on human samples, and that uses 33% less RAM when 8 CPU threads are used. Our tool can also calculate chromatin interaction potential matrices and generate open chromatin signals and interaction traces for cell groups. We demonstrate the utility of scATAK in an exploration of the chromatin regulatory landscape of a healthy adult human brain and show that it can reveal cell-type-specific features.

scATAK is available at https://github.com/pachterlab/scATAK/.

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 December 10, 2021.
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Efficient pre-processing of Single-cell ATAC-seq data
Fan Gao, Lior Pachter
bioRxiv 2021.12.08.471788; doi: https://doi.org/10.1101/2021.12.08.471788
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Efficient pre-processing of Single-cell ATAC-seq data
Fan Gao, Lior Pachter
bioRxiv 2021.12.08.471788; doi: https://doi.org/10.1101/2021.12.08.471788

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