Author

Yun Yan

The University of Texas MD Anderson Cancer CenterORCID 0000-0002-3701-9608Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Developmental Biology· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Assay:scRNA-seq· 3 Approach:statistical model· 3 Research Focus:clustering· 2 Research Focus:differential expression· 2 Organism:human· 2 Organism:mouse· 2 Research Focus:cell type annotation· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Aislyn P. SchalckiD· 1 shared Alejandro ContrerasiD· 1 shared Alexander DavisiD· 1 shared Anne M. Lynch· 1 shared Bora LimiD· 1 shared Cheng PengiD· 1 shared Danielle R. LittleiD· 1 shared Darlan Conterno MinussiiD· 1 shared

Activity by Year

2018-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperGenomics

Aislyn P. SchalckORCID

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3 papers

Recent·Most cited

Resolving clonal substructure from single cell genomic data using CopyKit

Darlan Conterno Minussi, Emi Sei, Junke Wang, Aislyn P. Schalck, Yun Yan, Alexander Davis, Hua‐Jun Wu, Shanshan Bai, Cheng Peng, Min Hu, Tod D. Casasent, Alejandro Contreras, Hui Chen, David Hui, Senthil Damodaran, , Nicholas E. Navin

CopyKit is a computational tool that resolves clonal substructure and reconstructs genetic lineages in tumors using single cell copy number data.

bioRxiv · Mar 9, 2022 · PreprintGenomics

Lung lineage transcription factor NKX2-1 epigenetically resolves opposing cell fates in vivo

Danielle R. Little, Anne M. Lynch, Yun Yan, Haruhiko Akiyama, Shioko Kimura, Jichao Chen

The paper shows NKX2-1 uses differential chromatin binding to resolve opposing cell fates in mouse lung progenitors, with YAP/TAZ loss altering its binding sites and leading to transcriptional changes.

Nature Communications · May 4, 2021Peer-reviewedDevelopmental Biology

K-nearest neighbor smoothing for high-throughput single-cell RNA-Seq data

Florian Wagner, Yun Yan, Itai Yanai

Aggregating UMI counts from a cell's nearest neighbours, chosen step-wise on variance-stabilised profiles, cuts technical noise enough that PCA and hierarchical clustering resolve cell types and T cell subsets.

bioRxiv · Apr 9, 2018 · PreprintBioinformatics✦ In-depth digest