Jane Liang, Ph.D.
Senior Biostatistician
Jane joined the QSU in June 2022 after completing her PhD in biostatistics at Harvard University. Her dissertation focused on statistical methodology and software development for clinical risk assessment in panel gene testing. Prior to grad school, she worked as a scientific programmer at the University of Tennessee Health Science Center, Department of Preventive Medicine, Division of Biostatistics.
Clinical area of interest:
Precision treatment, public health, oncology
Methodology area of interest:
Predictive modeling, statistical software, computational algorithms
Selected Publications:
Jane W. Liang, Gregory E. Idos, Christine Hong, Stephen B. Gruber, Giovanni Parmigiani, and Danielle Braun. Statistical methods for Mendelian models with multiple genes and cancers. Genetic Epidemiology, 2022. doi: 110.1002/gepi.22460.
Jane W. Liang and Śaunak Sen. Sparse matrix linear models for structured high-throughput data. The Annals of Applied Statistics, 16(1):169–192, 2022. doi: 10.1214/21-aoas1444.
Anne Marie McCarthy, Yi Liu, Sarah Ehsan, Zoe Guan, Jane W. Liang, Theodore Huang, Kevin Hughes, Alan Semine, Despina Kontos, Emily Conant, et al. Validation of breast cancer risk models by race/ethnicity, family history and molecular subtypes. Cancers, 14(1):45, 2022. doi:10.3390/cancers14010045.
Gavin Lee*, Jane W. Liang*, Qing Zhang, Theodore Huang, Christine Choirat, Giovanni Parmigiani, and Danielle Braun. Multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer with the novel R package PanelPRO. eLife, 10:e68699, 2021. doi: 10.7554/eLife.68699.
Yunqi Yang, Christine Hong, Jane W. Liang, Stephen Gruber, Giovanni Parmigiani, Gregory Idos*, and Danielle Braun*. A likelihood-based approach to assessing frequency of pathogenicity among variants of unknown significance (VUS) in susceptibility genes. Statistics in Medicine, 40(3):593– 606, 2020. doi: 10.1002/sim.8791.
Jane W. Liang, Robert J. Nichols, and Śaunak Sen. Matrix linear models for high-throughput chemical genetic screens. Genetics, 212(4):1063–1073, 2019. doi: 10.1534/genetics.119.302299.
Alexandra H. Bartlett, Jane W. Liang, Jose Vladimir Sandoval-Sierra, Jay H. Fowke, Eleanor M. Simonsick, Karen C. Johnson, and Khyobeni Mozhui. Longitudinal study of leukocyte DNA methylation and biomarkers for cancer risk in older adults. Biomarker Research, 7(1):1–13, 2019. doi: 10.1186/s40364-019-0161-3.
Hemant Gujar, Jane W. Liang, Nicholas C. Wong, and Khyobeni Mozhui. Profiling DNA methylation differences between inbred mouse strains on the Illumina Human Infinium MethylationEPIC microarray. PLOS ONE, 13(3):e0193496, 2018. doi: 10.1371/journal.pone.0193496.
*indicates equal contributions