Nancy R. Zhang

Dr. Zhang is Professor of Statistics and Data Science in The Wharton School at University of Pennsylvania.  Her current research focuses primarily on the development of statistical and computational approaches for the analysis of genetic, genomic, and transcriptomic data.  In the field of Genomics, she has developed methods to improve the accuracy of copy number variant and structural variant detection, methods for improved FDR control, and methods for analysis of single-cell RNA sequencing data.  In the field of Statistics, she has developed new models and methods for change-point analysis, variable selection, and model selection.  Dr. Zhang has also made contributions in the area of tumor genomics, where she has developed analysis methods to improve our understanding of intra-tumor clonal heterogeneity.

Dr. Zhang obtained her Ph.D. in Statistics in 2005 from Stanford University.  After one year of postdoctoral training at University of California, Berkeley, she returned to the Department of Statistics at Stanford University as Assistant Professor in 2006.  She received the Sloan Fellowship in 2011, before formally moving to University of Pennsylvania in 2012 as tenured Associate Professor.  She is the Principal Investigator in multiple independent research awards funded by the National institutes of Health and National Science Foundation.  She was rewarded a Medallion Lectureship by the Institute of Mathematical Statistics in 2021.  At Penn, she is a member of the Graduate Group in Genomics and Computational Biology and of the Penn Neurodegeneration Genomics Center.

Here are some of Dr. Zhang’s representative publications, categorized by topic (^ǂalphabetical ordering, *corresponding author):

• Change-point detection and scan statistics
  1. Zhang NR, Siegmund DO (2007) A modified Bayes information criterion with applications to the analysis of comparative genomic hybridization data, Biometrics 63, 22.
  2. Chan HP, Zhang NR ^ǂ (2007) Scan statistics with weighted observations, Journal of the American Statistical Association, 102, 595.
  3. Zhang NR, Siegmund DO, Ji H, Li J (2010) Detecting simultaneous changepoints in multiple sequences, Biometrika 97, 631.
  4. Siegmund DO, Zhang NR, Yakir B (2011) False discovery rate for scanning statistics, Biometrika 98, 979.
  5. Chen H, Zhang NR^ǂ (2015) Graph-based change-point detection, The Annals of Statistics 43, 139.
  6. Zhang NR, Siegmund DO (2012) Model selection for high dimensional, multi-sequence change-point problems, Statistica Sinica 22, 1507.
• General multiple testing control, high-dimensional inference
  1. Li F, Zhang NR^ǂ (2010) Bayesian variable selection in structured high-dimensional covariate spaces with applications in genomics, Journal of the American Statistical Association 105, 1202.
  2. Bickel PJ, Boley N, Brown JB, Huang H, Zhang NR ^ǂ (2010) Subsampling methods for genomic inference, Annals of Applied Statistics 4, 1660.
  3. Sun Y, Zhang NR and Owen A* (2012) Multiple hypothesis testing, adjusted for latent variables, with an application to the agemap gene expression data, Annals of Applied Statistics 6, 1664.
• DNA copy number estimation, variant detection and inference (see also the first bullet point which focuses more on the theory and methods aspect)
  1. Zhang NR, Senbabaoglu Y, Li J* (2010) Joint estimation of DNA copy number from multiple platforms, Bioinformatics 26, 153.
  2. Chen H, Xing H, Zhang NR* (2011) Estimation of parent specific DNA copy number in tumors using high-density genotyping arrays, PLoS Computational Biology 7, e1001060.
  3. Siegmund DO, Yakir B, Zhang NR* (2011) Detecting simultaneous variant intervals in aligned sequences, Annals of Applied Statistics 5, 645.
  4. Shen J, Zhang NR^* (2012) Change-point model on nonhomogeneous Poisson processes with application in copy number profiling by next-generation DNA sequencing, Annals of Applied Statistics 6, 476.
  5. Chen H, Bell JM, Zavala NA, Ji HP, Zhang NR* (2015) Allele-specific copy number profiling by next-generation DNA sequencing, Nucleic Acids Research 43, e23.
  6. Jiang Y, Oldridge DA, Diskin SJ, Zhang NR ^* (2015) CODEX: a normalization and copy number variation detection method for whole exome sequencing, Nucleic Acids Research 43, e39.
  7. Xia LC, Sakshuwong S, Hopmans ES, Bell JM, Grimes SM, Siegmund DO, Ji HP, Zhang NR^* (2016) A genome-wide approach for detecting novel insertion-deletion variants of mid-range size, Nucleic Acids Research 44, e126.
• Intra-tumor heterogeneity and cancer genomics (see also #2, 5, 7 under “DNA copy number estimation”)
  1. Jiang Y, Qiu Y, Minn AJ, Zhang NR* (2016) Assessing intratumor heterogeneity and tracking longitudinal and spatial clonal evolutionary history by next-generation sequencing, Proceedings of the National Academy of Sciences 113, E5528.
  2. Muralidharan O, Natsoulis G, Bell J, Ji H, Zhang NR* (2012) Detecting mutations in mixed sample sequencing data using empirical Bayes, Annals of Applied Statistics 6, 1047.
  3. Xia LC, Bell JM, Wood-Bouwens C, Chen JJ, Zhang NR*, Ji HP* (2017) Single molecule-based discovery of complex genomic rearrangements, Nucleic Acids Research 46, e19.
• Single cell genomics
  1. Jiang Y, Zhang NR*, Li M* (2017) SCALE: modeling allele-specific gene expression by single-cell RNA-sequencing, Genome Biology 18, 74.
  2. Jia C, Hu Y, Kelly D, Kim J, Li M*, Zhang NR* (2017) Accounting for technical noise in differential expression analysis of single-cell RNA sequencing data, Nucleic Acids Research, 45, 10978.
  3. Huang M, Wang J, Torre E, Dueck H, Shaffer S, Bonasio R, Murray J, Raj A, Li M, Zhang NR* (2018) SAVER: Gene expression recovery for single cell RNA sequencing, Nature Methods, 15, 539.
  4. Wang J, Huang M, Torre E, Dueck H, Shaffer S, Murray J, Raj A, Li M, Zhang NR* (2018) Gene expression distribution deconvolution in single cell RNA sequencing, accepted by Proceedings of the National Academy of Sciences.

For a complete overview of Dr. Zhang’s publications, funded grants, and teaching, mentoring, and service work, see her CV above.