Yun (Renee) Zhang, PhD

Assistant Professor
858-750-4003

Yun Zhang, PhD, is an assistant professor in the Informatics Department at the J. Craig Venter Institute (JCVI). She received an MMath in Mathematics and Statistics from the University of Oxford, UK, and a PhD in Statistics from the University of Rochester Medical Center. She also has industrial and research experience in Novartis Oncology and Mayo Clinic.

Dr. Zhang’s research interest includes statistical modeling and methodology development for big data produced by advanced biotechnologies. She is experienced in analyzing time-course microarray data, DNA methylation data, and microRNA sequencing data. She is also a professional developer of R and Bioconductor packages. Her recent focus is on applying statistical approaches to single cell RNA sequencing (scRNAseq) data.

Research Priorities

Mapping cell populations in scRNAseq data
  • Development of statistical approach for comparing new experimental data with cell type reference definitions to determine if new data represent existing or novel cell types
  • Development of statistically-comparable representation of reference cell types for the Human Cell Atlas
Gene set enrichment analysis (GSEA) pipelines with overlapping genes
  • Established pipeline FUNNEL-GSEA for time-course gene expression data using functional data analysis techniques
  • Development of data-driven method to empirically decompose the gene membership among multiple overlapped pathways
  • Extension of FUNNEL to data with limited time points, e.g. cross-sectional data, pre-post study, etc.
Investigation of tissue composition on gene co-expression
  • Investigation of the effect of composite cellular types on reconstruction of gene co-expression network
  • Application of deconvolution algorithm to tissue composition problems

Publications

Pinski AN, Steffen TL, Zulu MZ, George SL, Dickson A, Tifrea D, Maroney KJ, Tedeschi N, Zhang Y, Scheuermann RH, Pinto AK, Brien JD, Messaoudi I
Corticosteroid treatment in COVID-19 modulates host inflammatory responses and transcriptional signatures of immune dysregulation.
Journal of leukocyte biology. 2021-12-01; 110.6: 1225-1239.
PMID: 34730254
Aevermann BD, Shannon CP, Novotny M, Ben-Othman R, Cai B, Zhang Y, Ye JC, Kobor MS, Gladish N, Lee AH, Blimkie TM, Hancock RE, Llibre A, Duffy D, Koff WC, Sadarangani M, Tebbutt SJ, Kollmann TR, Scheuermann RH
Machine Learning-Based Single Cell and Integrative Analysis Reveals That Baseline mDC Predisposition Correlates With Hepatitis B Vaccine Antibody Response.
Frontiers in immunology. 2021-10-29; 12.690470.
PMID: 34777332
Bakken TE, Jorstad NL, Hu Q, Lake BB, Tian W, Kalmbach BE, Crow M, Hodge RD, Krienen FM, Sorensen SA, Eggermont J, Yao Z, Aevermann BD, Aldridge AI, Bartlett A, Bertagnolli D, Casper T, Castanon RG, Crichton K, Daigle TL, Dalley R, Dee N, Dembrow N, Diep D, Ding SL, Dong W, Fang R, Fischer S, Goldman M, Goldy J, Graybuck LT, Herb BR, Hou X, Kancherla J, Kroll M, Lathia K, van Lew B, Li YE, Liu CS, Liu H, Lucero JD, Mahurkar A, McMillen D, Miller JA, Moussa M, Nery JR, Nicovich PR, Niu SY, Orvis J, Osteen JK, Owen S, Palmer CR, Pham T, Plongthongkum N, Poirion O, Reed NM, Rimorin C, Rivkin A, Romanow WJ, Sedeño-Cortés AE, Siletti K, Somasundaram S, Sulc J, Tieu M, Torkelson A, Tung H, Wang X, Xie F, Yanny AM, Zhang R, Ament SA, Behrens MM, Bravo HC, Chun J, Dobin A, Gillis J, Hertzano R, Hof PR, Höllt T, Horwitz GD, Keene CD, Kharchenko PV, Ko AL, Lelieveldt BP, Luo C, Mukamel EA, Pinto-Duarte A, Preissl S, Regev A, Ren B, Scheuermann RH, Smith K, Spain WJ, White OR, Koch C, Hawrylycz M, Tasic B, Macosko EZ, McCarroll SA, Ting JT, Zeng H, Zhang K, Feng G, Ecker JR, Linnarsson S, Lein ES
Comparative cellular analysis of motor cortex in human, marmoset and mouse.
Nature. 2021-10-06; 598.7879: 111-119.
PMID: 34616062
Aevermann BD, Aevermann B, Zhang Y, Novotny M, Keshk M, Bakken TE, Bakken T, Miller J, Miller JA, Hodge RD, Hodge R, Lelieveldt B, Lein ES, Lein E, Scheuermann RH
A machine learning method for the discovery of minimum marker gene combinations for cell type identification from single-cell RNA sequencing.
Genome research. 2021-10-01; 31.10: 1767-1780.
PMID: 34088715
Zhang Y, Aevermann BD, Bakken TE, Miller JA, Hodge RD, Lein ES, Scheuermann RH
FR-Match: robust matching of cell type clusters from single cell RNA sequencing data using the Friedman-Rafsky non-parametric test.
Briefings in bioinformatics. 2021-07-20; 22.4:
PMID: 33249453
Brown DM, Zhang Y, Scheuermann RH
Epidemiology and Sequence-Based Evolutionary Analysis of Circulating Non-Polio Enteroviruses.
Microorganisms. 2020-11-25; 8.12:
PMID: 33255654
Mavian C, Pond SK, Marini S, Magalis BR, Vandamme AM, Dellicour S, Scarpino SV, Houldcroft C, Villabona-Arenas J, Paisie TK, Trovão NS, Boucher C, Zhang Y, Scheuermann RH, Gascuel O, Lam TT, Suchard MA, Abecasis A, Wilkinson E, de Oliveira T, Bento AI, Schmidt HA, Martin D, Hadfield J, Faria N, Grubaugh ND, Neher RA, Baele G, Lemey P, Stadler T, Albert J, Crandall KA, Leitner T, Stamatakis A, Prosperi M, Salemi M
Sampling bias and incorrect rooting make phylogenetic network tracing of SARS-COV-2 infections unreliable.
Proceedings of the National Academy of Sciences of the United States of America. 2020-06-09; 117.23: 12522-12523.
PMID: 32381734
Freire M, Moustafa A, Harkins DM, Torralba MG, Zhang Y, Leong P, Saffery R, Bockmann M, Kuelbs C, Hughes T, Craig JM, Nelson KE
Longitudinal Study of Oral Microbiome Variation in Twins.
Scientific reports. 2020-05-14; 10.1: 7954.
PMID: 32409670
Grifoni A, Sidney J, Zhang Y, Scheuermann RH, Peters B, Sette A
A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2.
Cell host & microbe. 2020-04-08; 27.4: 671-680.e2.
PMID: 32183941
Zhang Y, Cuerdo J, Halushka MK, McCall MN
The effect of tissue composition on gene co-expression.
Briefings in bioinformatics. 2019-12-08;
PMID: 31813949
Pessoa L, Aleti G, Choudhury S, Nguyen D, Yaskell T, Zhang Y, Li W, Nelson KE, Neto LLS, Sant'Ana ACP, Freire M
Host-Microbial Interactions in Systemic Lupus Erythematosus and Periodontitis.
Frontiers in immunology. 2019-11-12; 10.2602.
PMID: 31781106
Zhang Y, Bandyopadhyay G, Topham DJ, Falsey AR, Qiu X
Highly efficient hypothesis testing methods for regression-type tests with correlated observations and heterogeneous variance structure.
BMC bioinformatics. 2019-04-15; 20.1: 185.
PMID: 30987598
Zhang Y, Baheti S, Sun Z
Statistical method evaluation for differentially methylated CpGs in base resolution next-generation DNA sequencing data.
Briefings in bioinformatics. 2018-05-01; 19.3: 374-386.
PMID: 28040747
Zhang Y, Topham DJ, Thakar J, Qiu X
FUNNEL-GSEA: FUNctioNal ELastic-net regression in time-course gene set enrichment analysis.
Bioinformatics (Oxford, England). 2017-07-01; 33.13: 1944-1952.
PMID: 28334094

Research Priorities

Mapping cell populations in scRNAseq data
  • Development of statistical approach for comparing new experimental data with cell type reference definitions to determine if new data represent existing or novel cell types
  • Development of statistically-comparable representation of reference cell types for the Human Cell Atlas
Gene set enrichment analysis (GSEA) pipelines with overlapping genes
  • Established pipeline FUNNEL-GSEA for time-course gene expression data using functional data analysis techniques
  • Development of data-driven method to empirically decompose the gene membership among multiple overlapped pathways
  • Extension of FUNNEL to data with limited time points, e.g. cross-sectional data, pre-post study, etc.
Investigation of tissue composition on gene co-expression
  • Investigation of the effect of composite cellular types on reconstruction of gene co-expression network
  • Application of deconvolution algorithm to tissue composition problems

FR-Match: Robust Matching of Cell Type Clusters from Single Cell RNA Sequencing Data

17-Mar-2020
Blog

Coronavirus Pandemic: Putting Comprehensive Genomic Data in the Hands of Frontline Researchers Worldwide is Paramount

12-Mar-2020
Collaborator Release

LJI Scientists Identify Potential Targets for Immune Responses to Novel Coronavirus

The research, which includes comparative genomics analysis by JCVI scientists Yun Zhang and Richard Scheuermann, provides essential information about the human immune response to coronavirus infection that will guide the design and evaluation of diagnostics and vaccine candidates