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Systematic benchmarking of single-cell ATAC-sequencing protocols

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Item Type:Article
Title:Systematic benchmarking of single-cell ATAC-sequencing protocols
Creators Name:De Rop, F.V. and Hulselmans, G. and Flerin, C. and Soler-Vila, P. and Rafels, A. and Christiaens, V. and González-Blas, C.B. and Marchese, D. and Caratù, G. and Poovathingal, S. and Rozenblatt-Rosen, O. and Slyper, M. and Luo, W. and Muus, C. and Duarte, F. and Shrestha, R. and Bagdatli, S.T. and Corces, M.R. and Mamanova, L. and Knights, A. and Meyer, K.B. and Mulqueen, R. and Taherinasab, A. and Maschmeyer, P. and Pezoldt, J. and Lambert, C.L.G. and Iglesias, M. and Najle, S.R. and Dossani, Z.Y. and Martelotto, L.G. and Burkett, Z. and Lebofsky, R. and Martin-Subero, J.I. and Pillai, S. and Sebé-Pedrós, A. and Deplancke, B. and Teichmann, S.A. and Ludwig, L.S. and Braun, T.P. and Adey, A.C. and Greenleaf, W.J. and Buenrostro, J.D. and Regev, A. and Aerts, S. and Heyn, H.
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.
Source:Nature Biotechnology
Publisher:Nature Publishing Group
Date:3 August 2023
Official Publication:https://doi.org/10.1038/s41587-023-01881-x
PubMed:View item in PubMed

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