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      Systematic benchmarking of single-cell ATAC-sequencing protocols

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      1 , 2 , 1 , 2 , 1 , 2 , 3 , 4 , 1 , 2 , 1 , 2 , 4 , 4 , 1 , 5 , 6 , 6 , 6 , 7 , 8 , 7 , 8 , 9 , 10 , 11 , 11 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 17 , 18 , 4 , 19 , 4 , 20 , 21 , 22 , 23 , 24 , 24 , 3 , 25 , 26 , 27 , 20 , 21 , 4 , 19 , 28 , 17 , 18 , 11 , 29 , 6 , 15 , 16 , 13 , 14 , 12 , 9 , 30 , 7 , 8 , 5 , 31 , 32 , 1 , 2 , , 4 , 19 ,
      Nature Biotechnology
      Nature Publishing Group US
      Data processing, Epigenetics

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols.

          Abstract

          Benchmarking of scATAC-seq protocols demonstrates the effects of data quality on downstream analyses.

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          Most cited references35

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Cutadapt removes adapter sequences from high-throughput sequencing reads

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              Comprehensive Integration of Single-Cell Data

              Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.
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                Author and article information

                Contributors
                stein.aerts@kuleuven.be
                holger.heyn@cnag.crg.eu
                Journal
                Nat Biotechnol
                Nat Biotechnol
                Nature Biotechnology
                Nature Publishing Group US (New York )
                1087-0156
                1546-1696
                3 August 2023
                3 August 2023
                2024
                : 42
                : 6
                : 916-926
                Affiliations
                [1 ]VIB Center for Brain and Disease Research, ( https://ror.org/045c7t348) Leuven, Belgium
                [2 ]Department of Human Genetics, KU Leuven, ( https://ror.org/05f950310) Leuven, Belgium
                [3 ]GRID grid.10403.36, ISNI 0000000091771775, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), ; Barcelona, Spain
                [4 ]CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), ( https://ror.org/03wyzt892) Barcelona, Spain
                [5 ]Klarman Cell Observatory, Broad Institute of MIT and Harvard, ( https://ror.org/05a0ya142) Cambridge, MA USA
                [6 ]Broad Institute of MIT and Harvard, ( https://ror.org/05a0ya142) Cambridge, MA USA
                [7 ]Department of Stem Cell and Regenerative Biology, Harvard University, ( https://ror.org/03vek6s52) Cambridge, MA USA
                [8 ]Gene Regulation Observatory, Broad Institute of MIT and Harvard, ( https://ror.org/05a0ya142) Cambridge, MA USA
                [9 ]Department of Genetics, Stanford University, ( https://ror.org/00f54p054) Stanford, CA USA
                [10 ]GRID grid.249878.8, ISNI 0000 0004 0572 7110, Gladstone Institute of Neurological Disease, ; San Francisco, CA USA
                [11 ]Wellcome Sanger Institute, ( https://ror.org/05cy4wa09) Cambridge, UK
                [12 ]Department of Molecular and Medical Genetics, Oregon Health & Science University, ( https://ror.org/009avj582) Portland, OR USA
                [13 ]GRID grid.5288.7, ISNI 0000 0000 9758 5690, Division of Hematology & Medical Oncology, Knight Cancer Institute, , Oregon Health & Sciences University, ; Portland, OR USA
                [14 ]GRID grid.5288.7, ISNI 0000 0000 9758 5690, Division of Oncologic Sciences, Knight Cancer Institute, , Oregon Health & Sciences University, ; Portland, OR USA
                [15 ]GRID grid.484013.a, ISNI 0000 0004 6879 971X, Berlin Institute of Health at Charité–Universitätsmedizin Berlin, ; Berlin, Germany
                [16 ]Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), ( https://ror.org/04p5ggc03) Berlin, Germany
                [17 ]Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), ( https://ror.org/02s376052) Lausanne, Switzerland
                [18 ]Swiss Institute of Bioinformatics (SIB), ( https://ror.org/002n09z45) Lausanne, Switzerland
                [19 ]Universitat Pompeu Fabra (UPF), ( https://ror.org/04n0g0b29) Barcelona, Spain
                [20 ]GRID grid.418404.d, ISNI 0000 0004 0395 5996, Vitalant Research Institute, ; San Francisco, CA USA
                [21 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Department of Laboratory Medicine, , University of California, ; San Francisco, CA USA
                [22 ]Adelaide Centre for Epigenetics and the South Australian Immunogenomics Cancer Institute, Faculty of Health and Medical Sciences, The University of Adelaide, ( https://ror.org/00892tw58) Adelaide, South Australia Australia
                [23 ]GRID grid.1008.9, ISNI 0000 0001 2179 088X, University of Melbourne Centre for Cancer Research, , Victoria Comprehensive Cancer Centre, ; Melbourne, Victoria Australia
                [24 ]Digital Biology Group, Bio-Rad, ( https://ror.org/0379ygx07) Pleasanton, CA USA
                [25 ]Departament de Fonaments Clínics, Facultat de Medicina, Universitat de Barcelona, ( https://ror.org/021018s57) Barcelona, Spain
                [26 ]Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), ( https://ror.org/04hya7017) Madrid, Spain
                [27 ]Institució Catalana de Recerca i Estudis Avançats (ICREA), ( https://ror.org/0371hy230) Barcelona, Spain
                [28 ]GRID grid.425902.8, ISNI 0000 0000 9601 989X, ICREA, ; Barcelona, Spain
                [29 ]Department of Physics/Cavendish Laboratory, University of Cambridge, ( https://ror.org/013meh722) Cambridge, UK
                [30 ]Chan Zuckerberg Biohub, ( https://ror.org/00knt4f32) San Francisco, CA USA
                [31 ]Koch Institute of Integrative Cancer Research, ( https://ror.org/01xd6q208) Cambridge, MA USA
                [32 ]GRID grid.116068.8, ISNI 0000 0001 2341 2786, Howard Hughes Medical Institute, Department of Biology, , Massachusetts Institute of Technology (MIT), ; Cambridge, MA USA
                Author information
                http://orcid.org/0000-0001-5241-924X
                http://orcid.org/0000-0003-1883-871X
                http://orcid.org/0000-0003-1085-8062
                http://orcid.org/0000-0001-6313-3570
                http://orcid.org/0000-0002-7041-823X
                http://orcid.org/0000-0003-2779-0893
                http://orcid.org/0000-0002-1261-4929
                http://orcid.org/0000-0001-7465-7652
                http://orcid.org/0000-0001-5906-1498
                http://orcid.org/0000-0002-3903-7594
                http://orcid.org/0000-0001-7143-5691
                http://orcid.org/0000-0003-1757-7343
                http://orcid.org/0000-0002-0654-9147
                http://orcid.org/0000-0001-9264-6340
                http://orcid.org/0000-0002-5153-485X
                http://orcid.org/0000-0002-3728-6415
                http://orcid.org/0000-0001-8809-5195
                http://orcid.org/0000-0002-9896-9746
                http://orcid.org/0000-0001-9935-843X
                http://orcid.org/0000-0002-6294-6366
                http://orcid.org/0000-0002-2916-2164
                http://orcid.org/0000-0001-7648-8717
                http://orcid.org/0000-0003-1409-3095
                http://orcid.org/0000-0001-9958-3987
                http://orcid.org/0000-0003-3293-3158
                http://orcid.org/0000-0002-8006-0315
                http://orcid.org/0000-0002-3276-1889
                Article
                1881
                10.1038/s41587-023-01881-x
                11180611
                37537502
                eadb1a62-b88f-472e-951f-334fab95815f
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 18 January 2022
                : 22 June 2023
                Funding
                Funded by: H.H. received support for the project PID2020-115439GB-I00- funded by MCIN/AEI/ 10.13039/501100011033. This publication is also supported as part of a project (BCLLATLAS and ESPACE) that has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement No 810287 and 874710).
                Funded by: FundRef https://doi.org/10.13039/501100003130, Fonds Wetenschappelijk Onderzoek (Research Foundation Flanders);
                Award ID: 1S80920N
                Award ID: G0B5619N
                Award ID: G094121N
                Award Recipient :
                Funded by: M.R.C. is supported by the National Institutes on Aging K99/R00AG059918.
                Funded by: K.B.M. is supported by Wellcome (WT211276/Z/18/Z and Sanger core grant WT206194).
                Funded by: S.A.T. is supported by Wellcome (WT211276/Z/18/Z and Sanger core grant WT206194).
                Funded by: This work was supported by funding from the Rita Allen Foundation (W.J.G.), the Human Frontiers Science (RGY006S) (W.J.G.). W.J.G. is a Chan Zuckerberg Biohub investigator and acknowledges grants 2017-174468 and 2018-182817 from the Chan Zuckerberg Initiative, and the National Institutes of Health grants RM1-HG007735, UM1-HG009442, UM1-HG009436, R01- HG00990901, and U19- AI057266 (to W.J.G.). W.J.G. acknowledges funding from Emerson Collective.
                Funded by: This work was supported by an ERC Consolidator Grant to S.A. (no. 724226_cis- CONTROL), KU Leuven (grant no. C14/22/125 to S.A.), Foundation Against Cancer (grant no, F/2020/1396 to S.A.), F.W.O. (grants G0I2722N, G0B5619N and G094121N to S.A.), Aligning Science Across Parkinson’s (ASAP, grant no. ASAP-000430 to S.A.)
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                © Springer Nature America, Inc. 2024

                Biotechnology
                data processing,epigenetics
                Biotechnology
                data processing, epigenetics

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