Fast and Accurate Clustering of Single Cell Epigenomes Reveals Cis-Regulatory Elements in Rare Cell Types

Fang, R.; Preissl, S.; Hou, X.; Lucero, J.; Wang, X.; Motamedi, A.; Shiau, A. K.; Mukamel, E. A.; Zhang, Y.; Behrens, M. M.; Ecker, J.; Ren, B.

doi:10.1101/615179

bioRxiv · 10.1101/615179

Fast and Accurate Clustering of Single Cell Epigenomes Reveals Cis-Regulatory Elements in Rare Cell Types

Fang, R.·Preissl, S.·Hou, X.·Lucero, J.·Wang, X.·Motamedi, A.·Shiau, A. K.·Mukamel, E. A.·Zhang, Y.·Behrens, M. M.·Ecker, J.·Ren, B.

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Abstract

Identification of the cis-regulatory elements controlling cell-type specific gene expression patterns is essential for understanding the origin of cellular diversity. Conventional assays to map regulatory elements via open chromatin analysis of primary tissues is hindered by heterogeneity of the samples. Single cell analysis of transposase-accessible chromatin (scATAC-seq) can overcome this limitation. However, the high-level noise of each single cell profile and the large volumes of data could pose unique computational challenges. Here, we introduce SnapATAC, a software package for analyzing scATAC-seq datasets. SnapATAC can efficiently dissect cellular heterogeneity in an unbiased manner and map the trajectories of cellular states. Using the Nystrom method, a sampling technique that generates the low rank embedding for large-scale dataset, SnapATAC can process data from up to a million cells. Furthermore, SnapATAC incorporates existing tools into a comprehensive package for analyzing single cell ATAC-seq dataset. As demonstration of its utility, SnapATAC was applied to 55,592 single-nucleus ATAC-seq profiles from the mouse secondary motor cortex. The analysis revealed [~]370,000 candidate regulatory elements in 31 distinct cell populations in this brain region and inferred candidate transcriptional regulators in each of the cell types.

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Fang, R., Preissl, S., Hou, X., Lucero, J., Wang, X., Motamedi, A., Shiau, A. K., Mukamel, E. A., Zhang, Y., Behrens, M. M., Ecker, J., Ren, B.. 2019-04-22. Fast and Accurate Clustering of Single Cell Epigenomes Reveals Cis-Regulatory Elements in Rare Cell Types. https://doi.org/10.1101/615179

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