Guan'ao Yan

Ph.D. candidate in Statistics

Department of Statistics
University of California, Los Angeles

CV
Google Scholar
Email: gayan@g.ucla.edu

I am a PhD student in the Department of Statistics of University of California, Los Angeles (UCLA), under supervision of Dr. Jingyi Jessica Li. I obtained Master of Science in Statistics from Zhejiang University (ZJU), under supervision of Dr. Yi Zhang. Prior to that, I received Bachelor of Science in Mathematics and Bachelor of Economics from Shandong University.

My research interests lie in developing new statistical methods for understanding the real-world data. Specific research topics include

1. Statistical Bioinformatics

   1. Statistical methods for analyzing high-dimensional single-cell and spatial omics data

   2. Using synthetic data to enhance the statistical rigor in single-cell and spatial omics data analysis

2. General Statistical Methodologies: High-dimensional model inference and variable selection

3. Statistics in Education: Statistical method for promoting education equity (reported by Forbes and this podcast)

📣 News

• 2024/10/29: Our review on SVG detection is accepted at Nature Communications

• 2024/06/22: I received the UCLA Dissertation Year Fellowship

• 2023/11/02: Our work scReadSim is accepted at Nature Communications

• 2023/09/23: I received the JXTX + CSHL 2023 Genome Informatics Scholarship (first tier)

Publications

author*: equal distribution

Preprints

G. Yan, J.J. Li and M. Biggin (2024). Question-Score Identity Detection (Q-SID): A statistical algorithm to detect collusion groups with error quantification from exam question scores. arXiv. (Under review at Journal of the American Statistical Association) [Website] [Forbes article] [Podcast]

Z. Li, Z. M. Patel, D. Song, G. Yan, J. J. Li and L. Pinello (2023). Benchmarking computational methods to identify spatially variable genes and peaks. bioRxiv. (Under review at Nature Methods)

Peer reviewed

G. Yan, S. Hua and J.J. Li (2025). Categorization of 34 computational methods to detect spatially variable genes from spatially resolved transcriptomics data. Nature Communications, 16, 1141.

J. Zhao, F. Lao, G. Yan and Y. Zhang (2024). How data heterogeneity affects innovating knowledge and information in gene identification: A statistical learning perspective. Journal of Innovation & Knowledge, 9-3.

G. Yan, D. Song and J.J. Li (2023). scReadSim: a single-cell RNA-seq and ATAC-seq read simulator. Nature Communications, 14(1), 7428. [Software] [Website]

D. Song, Q. Wang, G. Yan, T. Liu and J.J. Li (2023). scDesign3 generates realistic in silico data for multimodal single-cell and spatial omics. Nature Biotechnology, 1-6. [Software]

S. Tang, H. Wang, G. Yan, L. Zhang (2022). Empirical likelihood based tests for detecting the presence of significant predictors in marginal quantile regression. Metrika, 1-31.

S. Chen*, G. Yan*, W. Zhang, J. Li, R. Jiang and Z. Lin (2021). RA3 is a reference-guided approach for epigenetic characterization of single cells. Nature Communications, 12(1), 1-13. [Software]

J. Zhao, G. Yan and Y. Zhang (2021). Robust estimation and shrinkage in ultrahigh dimensional expectile regression with heavy tails and variance heterogeneity. Statistical Papers, 1-28.

J. Zhao*, G. Yan* and Y. Zhang (2019). Semiparametric expectile regression for high-dimensional heavy-tailed and heterogeneous data. arXiv. (Accepted at Applied Mathematics-A Journal of Chinese Universities)

Patents

Mark Douglas Biggin, Jingyi Li, Guan'ao Yan. Systems and methods for detecting collusion in student testing using graded scores or answers for individual questions (Serial No. 17/450,984; US Patent 11,915,615 B2, filed Feburary 17, 2024)

Presentations

Oral Presentations

• NHGRI Genome Tech Dev Coordinating Center Working Group, Jackson Laboratory, USA (01/2025)

• Department of Mathematical Sciences, New Jersey Institute of Technology, USA (12/2024)

• Department of Statistics and Data Sciences, University of California, Los Angeles, USA (11/2024)

• Joint Statistical Meetings, Portland, USA (08/2024)

• Institute for Computational and Experimental Research in Mathematics, Providence, USA (12/2023)

• Jonsson Comprehensive Cancer Center Gene Regulation Seminar, Los Angeles, USA (11/2023)

• Institute for Quantitative and Computational Biosciences Research Seminar, Los Angeles, USA (12/2022)

• NSF-Simons Center for Multiscale Cell Fate 5th Annual Symposium, Irvine, USA (10/2022)

• The 7th International Conference on Statistics and Probability, IMS-China, Dalian, China (07/2019)

Poster Presentations

• Cold Spring Harbor Laboratory Genome Informatics Conference, New York, USA (12/2023)

• RECOMB/ISCB Conference on Regulatory & Systems Genomics, Los Angeles, USA (11/2023)

• Chan Zuckerberg Initiative Single-Cell Biology 2023 Annual Meeting, Carlsbad, USA (11/2023)

• ISMB/ECCB, Lyon, France (07/2023)

• Los Angeles Bioscience Ecosystem Summit, Los Angeles, USA (05/2023)

• Jonsson Comprehensive Cancer Center Retreat Poster Session, Los Angeles, USA (05/2023)

• Institute for Quantitative and Computational Biosciences Poster Session, Los Angeles, USA (09/2022)

Teaching

Teaching assistant

• UCLA STATS 205 Hierarchical Linear Models (Spring 2024)

• UCLA STATS 203 Large Sample Theory (Winter 2024)

• ElevatePro Statistical Science with Applications to Epidemiology (Summer 2021)

• ZJU MATH 1001 Advanced Mathematics (Fall 2018 & 2019)

Workshop instructor

• Presenter, Jonsson Comprehensive Cancer Center Workshop, UCLA (Dec 2024)
  “Categorization of 34 Computational Methods to Detect Spatially Variable Genes from Spatially Resolved Transcriptomics Data”

• Coordinator & Presenter, QCBio Workshop, UCLA (May 2022)
  “Statistical Methods for Enhancing the Rigor in Single-cell RNA-seq Data Analysis”

Guest lecturer

• UCLA STATS 205 Hierarchical Linear Models (Spring 2024)

• UCLA BIOINFO 229 Current Topics in Bioinformatics (Winter 2024)

Undergraduate student mentor

• Weijian Wang, Undergraduate student at Zhejiang University (12/2022 - )

• Zhiyin Liu, Undergraduate student at Hong Kong University of Science and Technology (12/2022 - )

• Shuo Hua, Undergraduate student at Tsinghua University (06/2022 - 12/2022)

“If we all worked on the assumption that what is accepted as true is really true, there would be little hope of advance.”

- Orville Wright