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

Gao, F.; Pachter, L.

doi:10.1101/2021.12.08.471788

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bioRxiv · 10.1101/2021.12.08.471788

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

Gao, F.·Pachter, L.

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Abstract

Single-cell and single-nucleus genomics assays are becoming increasingly complex, with multiple measurements of distinct modalities performed concurrently resulting in "multimodal" readouts. While multimodal single-cell and single-nucleus genomics offers the potential to better understand how distinct cellular processes are coordinated, there can be technical and cost tradeoffs associated with increasing the number of measurement modes. To assess some of the tradeoffs inherent in multimodal assays, we have developed snATAK for preprocessing sequencing-based high-throughput assays that measure single-nucleus chromatin accessibility. Coupled with kallisto bustools for single-nucleus RNA-seq preprocessing, the snATAK workflow can be used for uniform preprocessing of 10x Genomics Multiome and single-nucleus ATAC-seq, SHARE-seq, ISSAAC-seq, spatial ATAC-seq and other chromatin-related assays. Using snATAK, we are able to perform cross-platform comparisons and quantify some of the tradeoffs between Multiome and unregistered single-nucleus RNA-seq/ATAC-seq experiments. We also show that snATAK can be used to assess allele concordance between paired RNAseq and ATACseq. snATAK is available at https://github.com/pachterlab/snATAK/.

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Gao, F., Pachter, L.. 2021-12-10. Efficient pre-processing of Single-cell ATAC-seq data. https://doi.org/10.1101/2021.12.08.471788

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