The Multi-omics Data Integration Research Pillar in the Division of Biostatistics is dedicated to advancing biomedical research by developing innovative statistical and computational methodologies and application pipelines for multi-omics data analysis, integration, and study design. The group focuses on understanding molecular disease mechanisms through cutting-edge research topics, including causal inference in omics data, such as constructing causal molecular networks and performing causal mediation analysis. It also explores the use of machine learning and artificial intelligence methods to integrate multi-omics and multi-modal data for disease prediction and risk modeling. Additionally, the team develops comprehensive analytic pipelines to investigate the interplay between the environment, microbiome, and host.

To foster engagement and knowledge exchange, the group hosts the monthly Multi-omics Data Analysis Journal Club on the fourth Friday of each month from 11:00AM to 12:00PM. During these sessions, a group member leads a discussion on a recent publication in the multi-omics research field, encouraging collaboration and exploration of emerging trends.

Lead Faculty

Jiyuan Hu, PhD
Assistant Professor

Huilin Li, PhD
Professor

Faculty Members

Hakhamanesh Mostafavi, PhD
Assistant Professor

Chan Wang, PhD
Research Assistant Professor

Our Methodology Research

• Hu J, Wang C, Blaser MJ, Li H. Joint modeling of zero-inflated longitudinal proportions and time-to-event data with application to a gut microbiome study. Biometrics. 2022 Dec;78(4):1686-1698.
• Wang C, Ahn J, Tarpey T, Yi SS, Hayes RB, Li H. A microbial causal mediation analytic tool for health disparity and applications in body mass index. Microbiome. 2023 Jul 27;11(1):164.
• Li Z, Yu X, Guo H, Lee T, Hu J. A maximum-type microbial differential abundance test with application to high-dimensional microbiome data analyses. Frontiers in Cellular and Infection Microbiology, 12(2022): 988717.

Our Collaborative Research

• Cox LM, Yamanishi S, Sohn J, Alekseyenko AV, Leung JM,  Cho I, Kim S, Li H, Gao Z, Mahana D,  Zárate Rodriguez GZ.,  Rogers AB,  Robine N,  Loke P,  Blaser MJ. (2014) Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences. Cell. 2014 Aug 14, 705–721.
• Tsay JJ, Wu BG, Sulaiman I, Gershner K, Schluger R, Li Y, Yie TA, Meyn P, Olsen E, Perez L, Franca B, Carpenito J, Iizumi T, El-Ashmawy M, Badri M, Morton JT, Shen N, He L, Michaud G, Rafeq S, Bessich JL, Smith RL, Sauthoff H, Felner K, Pillai R, Zavitsanou AM, Koralov SB, Mezzano V, Loomis CA, Moreira AL, Moore W, Tsirigos A, Heguy A, Rom WN, Sterman DH, Pass HI, Clemente JC, Li H, Bonneau R, Wong KK, Papagiannakopoulos T, Segal LN. Lower Airway Dysbiosis Affects Lung Cancer Progression. Cancer Discovery. 2021 Feb;11(2):293-307. 
• Barrett TJ, Distel E, Murphy AJ, Hu J, Garshick MS, Ogando Y, Liu J, Vaisar T, Heinecke JW, Berger JS, Goldberg IJ. Apolipoprotein AI) promotes atherosclerosis regression in diabetic mice by suppressing myelopoiesis and plaque inflammation. Circulation. 2019 Oct 1;140(14):1170-84.

Contact Us

For more information about the Multi-omics Data Integration Research Pillar, please contact Huilin Li, PhD, at Huilin.Li@NYULangone.org.