Author

Zhijun Duan

University of Washington

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

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Biology Disciplines

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Genomics· 4 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 4 Assay:Hi-C· 4 Organism:human· 2 Organism:mouse· 2 Assay:scRNA-seq· 2 Approach:statistical model· 2 Assay:ATAC-seq· 1 Research Focus:batch correction / integration· 1

Frequent Co-Authors

Jay ShendureiD· 5 shared Xinxian DengiD· 5 shared Choli LeeiD· 4 shared Christine M. DistècheiD· 4 shared Vijay RamaniiD· 4 shared William Stafford NobleiD· 4 shared Giancarlo BonoraiD· 2 shared He FangiD· 2 shared

Activity by Year

2017-2021 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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5 shared papersGenomics

Jay ShendureORCID

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5 papers

Recent·Most cited

Single-cell landscape of nuclear configuration and gene expression during stem cell differentiation and X inactivation

Giancarlo Bonora, Vijay Ramani, Ritambhara Singh, He Fang, Dana L. Jackson, Sanjay R Srivatsan, Ruolan Qiu, Choli Lee, Cole Trapnell, Jay Shendure, Zhijun Duan, Xinxian Deng, William Stafford Noble, Christine M. Distèche

The paper integrates single-cell RNA-seq, ATAC-seq, and Hi-C data to study nuclear configuration and gene expression changes during stem cell differentiation and X inactivation, revealing discrete structural changes and delayed chromatin compaction.

Genome biology · Sep 27, 2021Peer-reviewedGenomics

Unsupervised manifold alignment for single-cell multi-omics data

Ritambhara Singh, Pınar Demetçi, Giancarlo Bonora, Vijay Ramani, Choli Lee, He Fang, Zhijun Duan, Xinxian Deng, Jay Shendure, Christine M. Distèche, William Stafford Noble

This paper applies and extends MMD-MA to align single-cell transcriptome and chromatin accessibility data from ~2000 cells, demonstrating its scalability and accuracy.

ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) · Sep 21, 2020Peer-reviewedBioinformatics

Sci-Hi-C: a single-cell Hi-C method for mapping 3D genome organization in large number of single cells

Vijay Ramani, Xinxian Deng, Ruolan Qiu, Choli Lee, Christine M. Distèche, William Stafford Noble, Jay Shendure, Zhijun Duan

Sci-Hi-C is a single-cell Hi-C method that maps 3D genome organization in large numbers of single cells, enabling analysis of chromatin interactions and cellular variability.

Methods · Sep 16, 2019Peer-reviewedGenomics

Using DNase Hi-C techniques to map global and local three-dimensional genome architecture at high resolution

Wenxiu Ma, Ferhat Ay, Choli Lee, Günhan Gülsoy, Xinxian Deng, Savannah M. Cook, Jennifer Hesson, Christopher Cavanaugh, Carol B. Ware, Anton Krumm, Jay Shendure, C. Anthony Blau, Christine M. Distèche, William Stafford Noble, ZhiJun Duan

This paper introduces DNase Hi-C and targeted DNase Hi-C methods for high-resolution mapping of chromatin interactions, overcoming limitations of traditional Hi-C techniques.

Methods · Jan 31, 2018Peer-reviewedGenomics

Massively multiplex single-cell Hi-C

Vijay Ramani, Xinxian Deng, Kevin L Gunderson, Frank J Steemers, Christine M Disteche, William S Noble, Zhijun Duan, Jay Shendure

This paper introduces combinatorial single cell Hi-C, a method for measuring chromosome conformation in single cells, and shows its ability to distinguish cell types and reveal chromosomal heterogeneity.

Nature Methods · Jan 30, 2017Peer-reviewedGenomics