Lida Wang

Bio

I am a Postdoctoral Research Fellow at the Dana-Farber Cancer Institute and Harvard Medical School, working with Prof. Alexander Gusev. My research focuses on statistical genetics, functional genomics, and data science.

I completed my Ph.D. in Biostatistics at Penn State University, advised by Prof. Dajiang Liu and closely collaborated with Prof. Laura Carrel. In the summer of 2023, I interned as a Research Data Scientist at Calico, a subsidiary of Alphabet, where I worked with Dr. Madeleine Cule and her team.

Prior to my Ph.D., I earned a master’s degree in Biostatistics from Georgetown University, where I was advised by Prof. Ao Yuan and Ming Tan. I got my bachelor’s degree in Mathematics and Applied Mathematics from the Southern University of Science and Technology, where I was mentored by Prof. Guoliang Tian.

My CV is here.

Research Interests

Developing models to characterize eQTL architecture at single-cell resolution, enabling a deeper understanding of cell-type/state–specific gene regulation.
Leveraging genetic and electronic health record (EHR) data with statistical methods and LLM to predict disease progression.

Projects

Nature Communications

Axis-QTL: Bulk And Single cell eQTL Integration across Cell states (BASIC)

Lida Wang, Shuang Gao, Dajiang Liu, 2025

*ASHG 2025 U.S. resource limited award

*ASHG 2025 reviewer's choice abstract

NC 2025 Abstract Package
Cell Genomics

JOint analysis of Bulk-eQTL and Sc-eQTL (JOBS)

Lida Wang, Havell Markus, Dajiang Liu, 2025.

*ASHG 2023 Featured Plenary Talk

*ASHG 2023 Predoctoral Trainee Research Excellence Finalist

*ACGA Predoctoral Trainee Awardee for Basic Research

CG 2025 Abstract Package
Nature Communications

EXpression PREdiction with Summary Statistics Only (EXPRESSO)

Lida Wang, Chachrit Khunsriraksakul, Dajiang Liu, 2024

*STATGEN 2024 Invited Talk

*ASHG 2022 poster presentation

NC 2024 Package Poster
Nature Communications

Prediction Using Models Informed by Chromatin conformations and Epigenomics (PUMICE)

Chachrit Khunsriraksakul, Lida Wang, Dajiang Liu, 2022

*ASHG 2020 Reviewer’s choice abstract

*PQG 2020 conference honorable mention

NC 2022 NC 2023 NC 2024 AJHG 2026 Package GitHub
Statistics in Medicine

Set-regression with applications to subgroup analysis

Ao Yuan, Lida Wang, Ming Tan, 2021

SIM 2021

Selected Publication

[2025] Wang, L.†, Gao, S.†, et al. Integrating axis quantitative trait loci looks beyond cell types and offers insights into brain-related traits. Nat Commun 16, 10606 (2025)
[2025] Wang, L.†, Markus, H.†, et al. An atlas of single-cell eQTLs dissects autoimmune disease genes and identifies novel drug classes for treatment. Cell Genomics (2025)
[2024] Wang, L.†, Khunsriraksakul, C.†, et al. Integrating single cell expression quantitative trait loci summary statistics to understand complex trait risk genes. Nat Commun 15, 4260 (2024)
[2022] Yuan, A., Wang, L., Tan, MT. Set-regression with applications to subgroup analysis. Statistics in Medicine. 2022;41(1):180-193.

Resources

[2025] Penn State News features our BASIC work.
[2025] Penn State News features our JOBS work.
[2024] AMSTATS News [1] [2] spotlight on Dr. Wang.
[2024] Penn State News features our EXPRESSO work.
[2022] Penn State News and Penn State Health News features our PUMICE work.

Contact

Address: 375 Longwood Ave, Boston, MA
Email: lida.wang.96 (at) gmail.com