Musu Yuan 袁睦苏

I am a Postdoctoral fellow in DBEI, PSOM at University of Pennsylvania, Philadelphia, advised by Professor Mingyao Li. I used to be a visiting student in her lab in 2024. Previously, I received my Ph.D. digree in integrated life sciences in July 2026 from Academy for Advanced Interdisciplinary Studies, Peking University, advised by Dr.Minghua Deng. Before that, I received my B.S. degree in statistics in July 2021 from School of Mathematical Science, Peking University. I participated in the 32nd Chinese Mathematical Olympiad(CMO) in 2016 when I was in Wuhan's No.2 high school. Contact DBEI, PSOM University of Pennsylvania, Philadelphia Email (1): musu.yuan ᴀᴛ pennmedicine.upenn.edu Email (2): musu990519 ᴀᴛ gmail.com

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Research Interests

My research interest lies in the broad fields of biostatistics.
I mainly work on developing statistic models for single-cell omics data, spatial transcriptome data and morphology data.

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Publications

1. Smart spatial omics (S2-omics) optimizes region of interest selection to capture molecular heterogeneity in diverse tissues
   Musu Yuan, Kaitian Jin, Hanying Yan, Amelia Schroeder, Chunyu Luo, Sicong Yao, Bernhard Dumoulin, Jonathan Levinsohn, Tianhao Luo, Jean R. Clemenceau, Inyeop Jang, Minji Kim, Yunhe Liu, Minghua Deng, Emma E. Furth, Parker Wilson, Anupma Nayak, Idania Lubo, Luisa Maren Solis Soto, Linghua Wang, Jeong Hwan Park, Katalin Susztak, Tae Hyun Hwang, Mingyao Li^*
   Nature Cell Biology (2025), https://doi.org/10.1038/s41556-025-01811-w
   
2. Improving Tree Probability Estimation with Stochastic Optimization and Variance Reduction
   Tianyu Xie^†, Musu Yuan^†, Minghua Deng, Cheng Zhang^*
   Statistics and Computing, Volume 34, article number 186, (2024)
   
3. scPLAN: A hierarchical computational framework for single transcriptomics data annotation, integration and cell-type label refinement
   Qirui Guo^†, Musu Yuan^†, Lei Zhang^*, Minghua Deng^*
   Briefings in Bioinformatics, Volume 25, Issue 4, July 2024, bbae305
   
4. SPANN: Annotating single-cell resolution spatial transcriptome data with scRNA-seq data
   Musu Yuan^†, Hui Wan^†, Minghua Deng^*
   Briefings in Bioinformatics, Volume 25, Issue 2, March 2024, bbad533
   
5. Continually adapting pretrained language model to universal annotation of single-cell RNA-seq data
   Hui Wan, Musu Yuan, Yiwei Fu, Minghua Deng^*
   Briefings in Bioinformatics, Volume 25, Issue 2, March 2024, bbae047
   
6. Clustering single-cell multi-omics data with MoClust
   Musu Yuan, Liang Chen^*, Minghua Deng^*
   Bioinformatics, Volume 39, Issue 1, January 2023, btac736
7. Clustering CITE-seq data with a canonical correlation-based deep learning method
   Musu Yuan, Liang Chen, Minghua Deng^*
   Frontiers in Genetics, Volume 13 - 2022
8. scMRA: a robust deep learning method to annotate scRNA-seq data with multiple reference datasets
   Musu Yuan^†, Liang Chen^†, Minghua Deng^*
   Bioinformatics, Volume 38, Issue 3, February 2022, Pages 738–745

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Preprints

1. HistoSweep enables cellular-resolution tissue quality control for gigapixel images in digital pathology and spatial omics
   Amelia Schroeder, Xiaokang Yu, Wei Li, Liran Mao, Musu Yuan, Jiyuan Yang, Nadja Sachs, Bernhard Dumoulin, George X. Xu, Xunda Luo, Alexander Huang, Katalin Susztak, Tae Hyun Hwang, Humam Kadara, Lars Maegdefessel, Jiyang Yu, Mingyao Li^*
   bioRxiv
   
2. Multiscale confidence quantification for virtual spatial transcriptomics with UTOPIA
   Kaitian Jin, Zihao Chen, Xiaokang Yu, Musu Yuan, Amelia Schroeder, Bernhard Dumoulin, Yunhe Liu, Linghua Wang, Jeong Hwang Park, Tae Hyun Hwang, Katalin Susztak, Zhimei Ren, Nancy Zhang, Mingyao Li^*
   bioRxiv
   

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