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dc.contributor.authorHu, Kai
dc.contributor.authorLiu, Haibo
dc.contributor.authorLawson, Nathan D
dc.contributor.authorZhu, Lihua Julie
dc.date.accessioned2023-05-24T13:21:28Z
dc.date.available2023-05-24T13:21:28Z
dc.date.issued2022-09-27
dc.identifier.citationHu K, Liu H, Lawson ND, Zhu LJ. scATACpipe: A nextflow pipeline for comprehensive and reproducible analyses of single cell ATAC-seq data. Front Cell Dev Biol. 2022 Sep 27;10:981859. doi: 10.3389/fcell.2022.981859. PMID: 36238687; PMCID: PMC9551270.en_US
dc.identifier.issn2296-634X
dc.identifier.doi10.3389/fcell.2022.981859en_US
dc.identifier.pmid36238687
dc.identifier.urihttp://hdl.handle.net/20.500.14038/52102
dc.description.abstractSingle cell ATAC-seq (scATAC-seq) has become the most widely used method for profiling open chromatin landscape of heterogeneous cell populations at a single-cell resolution. Although numerous software tools and pipelines have been developed, an easy-to-use, scalable, reproducible, and comprehensive pipeline for scATAC-seq data analyses is still lacking. To fill this gap, we developed scATACpipe, a Nextflow pipeline, for performing comprehensive analyses of scATAC-seq data including extensive quality assessment, preprocessing, dimension reduction, clustering, peak calling, differential accessibility inference, integration with scRNA-seq data, transcription factor activity and footprinting analysis, co-accessibility inference, and cell trajectory prediction. scATACpipe enables users to perform the end-to-end analysis of scATAC-seq data with three sub-workflow options for preprocessing that leverage 10x Genomics Cell Ranger ATAC software, the ultra-fast Chromap procedures, and a set of custom scripts implementing current best practices for scATAC-seq data preprocessing. The pipeline extends the R package ArchR for downstream analysis with added support to any eukaryotic species with an annotated reference genome. Importantly, scATACpipe generates an all-in-one HTML report for the entire analysis and outputs cluster-specific BAM, BED, and BigWig files for visualization in a genome browser. scATACpipe eliminates the need for users to chain different tools together and facilitates reproducible and comprehensive analyses of scATAC-seq data from raw reads to various biological insights with minimal changes of configuration settings for different computing environments or species. By applying it to public datasets, we illustrated the utility, flexibility, versatility, and reliability of our pipeline, and demonstrated that our scATACpipe outperforms other workflows.en_US
dc.language.isoenen_US
dc.relation.ispartofFrontiers in Cell and Developmental Biologyen_US
dc.relation.urlhttps://doi.org/10.3389/fcell.2022.981859en_US
dc.rights© 2022 Hu, Liu, Lawson and Zhu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.en_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectchromatin accessibilityen_US
dc.subjectintegration of scATAC-seq and scRNA-seqen_US
dc.subjectnextflowen_US
dc.subjectpipelineen_US
dc.subjectscATAC-seqen_US
dc.subjectsingle cellen_US
dc.subjecttrajectory inferenceen_US
dc.subjecttranscription factor activity and footprinting analysisen_US
dc.titlescATACpipe: A nextflow pipeline for comprehensive and reproducible analyses of single cell ATAC-seq dataen_US
dc.typeJournal Articleen_US
dc.source.journaltitleFrontiers in cell and developmental biology
dc.source.volume10
dc.source.beginpage981859
dc.source.endpage
dc.source.countrySwitzerland
dc.identifier.journalFrontiers in cell and developmental biology
refterms.dateFOA2023-05-24T13:21:29Z
dc.contributor.departmentMolecular, Cell and Cancer Biologyen_US
dc.contributor.departmentProgram in Molecular Medicineen_US


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© 2022 Hu, Liu, Lawson and Zhu. This is
an open-access article distributed
under the terms of the Creative
Commons Attribution License (CC BY).
The use, distribution or reproduction in
other forums is permitted, provided the
original author(s) and the copyright
owner(s) are credited and that the
original publication in this journal is
cited, in accordance with accepted
academic practice. No use, distribution
or reproduction is permitted which does
not comply with these terms.
Except where otherwise noted, this item's license is described as © 2022 Hu, Liu, Lawson and Zhu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.