Yun Deng

Postdoc at Stanford University

I am mainly interested in developing mathematical and computational methods to unveil novel insights from increasing rich biological datasets. Recently, I am particularly interested in developing next-generation computational methods for evolutionary biology and population genetics, to achieve what previous methods cannot do. Here are some topics which my research focuses on:

Inference and analysis of Ancestral Recombination Graphs (ARGs)

A core line of research in the group is the development of computational methods for Ancestral Recombination Graphs (ARGs), a revolutionizing framework in population and evolutionary genetics that goes well beyond the capabilities of summary-statistics-based inference.

I develop robust and accurate computational methods for inferring ARGs and aim at using them for novel population-genetic analysis. These efforts have resulted in methods including SINGER and POLEGON.

Ancestral Recombination Graph research

Selected Publications

  1. Deng, Y., Nielsen, R., & Song, Y. S. (2025). Robust and accurate Bayesian inference of genome-wide genealogies for hundreds of genomes. Nature Genetics.

  2. Deng, Y., DeWitt, W. S., Song, Y. S., & Nielsen, R. (2025). A general framework for branch length estimation in Ancestral Recombination Graphs. PNAS.

  3. Nielsen, R., Vaughn, A. H., & Deng, Y. (2025). Inference and applications of ancestral recombination graphs. Nature Reviews Genetics.

Population structure and demographic history

Understanding population structure and demographic history is fundamental to population genetics. Patterns of genetic variation observed today reflect histories of population size changes, splits, migration, and admixture.

I develop statistical and computational methods to reconstruct these processes from genomic data, with a particular interest in extracting information across different timescales. I am especially interested in identifying new signals that can overcome limitations of classical approaches.

Population structure and demographic history

Selected publications

  1. Deng, Y., Pritchard, J. K., & Spence, J. P. (2026). Coalescent-Based Time-Stratified Statistics Reveal Population Structure Dynamics using the Ancestral Recombination Graph. bioRxiv.

  2. Deng, Y., Nielsen, R., & Song, Y. S. (2025). A previously reported bottleneck in human ancestry 900 kya is likely a statistical artifact. Genetics, 229(1), iyae192.