Author

Dmitry Pokholok

Illumina (United States)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genomics· 2 Genetics· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 3 Organism:human· 3 Organism:mouse· 2 Assay:scATAC-seq· 2 Research Focus:cell type annotation· 1 Assay:DNA methylation· 1 Research Focus:genome assembly· 1 Assay:Hi-C· 1

Frequent Co-Authors

Frank J. Steemers· 3 shared Andrew AdeyiD· 2 shared Brian J. O’RoakiD· 2 shared Ryan M. MulqueeniD· 2 shared Andrew J. FieldsiD· 1 shared Andrew S. Kohlway· 1 shared Brendan L. O’ConnelliD· 1 shared Caleb A. LareauiD· 1 shared

Activity by Year

2018-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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3 shared papersGenomics

Frank J. Steemers

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3 papers

Recent·Most cited

High-content single-cell combinatorial indexing

Ryan M. Mulqueen, Dmitry Pokholok, Brendan L. O’Connell, Casey A. Thornton, Fan Zhang, Brian J. O’Roak, Jason M. Link, Galip Gürkan Yardımcı, Rosalie C. Sears, Frank J. Steemers, Andrew Adey

This paper introduces a novel adaptor-switching strategy, s3, that significantly improves usable reads per cell in single-cell genomics assays while maintaining high-throughput capabilities.

Nature Biotechnology · Jul 5, 2021Peer-reviewedGenetics

Droplet-based combinatorial indexing for massive scale single-cell epigenomics

Caleb A. Lareau, Fabiana M. Duarte, Jennifer G. Chew, Vinay K. Kartha, Zach D. Burkett, Andrew S. Kohlway, Dmitry Pokholok, Martin J. Aryee, Frank J. Steemers, Ronald Lebofsky, Jason Daniel Buenrostro

The paper introduces a droplet-based combinatorial indexing method for high-throughput scATAC-seq, enabling large-scale single-cell chromatin accessibility profiling in mouse and human cells.

bioRxiv · Apr 18, 2019 · PreprintGenomics

Scalable and efficient single-cell DNA methylation sequencing by combinatorial indexing.

Ryan M. Mulqueen, Dmitry Pokholok, Steven J Norberg, Kristof A. Torkenczy, Andrew J. Fields, Duanchen Sun, John R. Sinnamon, Jay Shendure, Cole Trapnell, Brian J. O’Roak, Zheng Xia, Frank J. Steemers, Andrew Adey

The paper introduces sci-MET, a scalable single-cell DNA methylation sequencing method, achieving 69% read alignment rates and successfully deconvolving a mixture of three human cell lines.

Nature Biotechnology · Apr 9, 2018Peer-reviewedGenomics