Statistical methods for single-cell and spatial RNA-seq

Dr. Christina Kendziorski's research concerns statistical methods and software for computational biology and genomics. Her group develops statistical methods and software for the analysis of data from high-throughput genomics experiments and have considerable expertise in the experimental design and analysis of bulk RNA-seq studies and in single-cell RNA-seq. The group also uses high-throughput data from... Read more »

Statistical analysis of spatial expression pattern for spatially resolved transcriptomic studies

Dr. Xiang Zhou is a John G. Searle Assistant Professor of biostatistics who received his M.S. in statistics and PhD in neurobiology from Duke University (2010). His research focuses on developing statistical methods and computational tools for genetic and genomic studies. These studies often involve large-scale and high-dimensional data; examples include genome-wide association studies and... Read more »

Towards a unified methodology of study design and statistical analysis for causal inference in implementation science

Dr. Donna Spiegelman has a joint doctorate in biostatistics and epidemiology and her research is motivated by problems that arise in epidemiology and require biostatistical settlement; in part a focus on troubleshooting methods for study design and data analysis to reduce bias in estimation and inference due to measurement error or misclassification in the exposure... Read more »

Robust testing for differential abundance in microbiome data

Please note the changed time of day for this Seminar: 2-3 pm. The Biostatistics Department Awards Day will commence directly after the seminar. Dr. Yijuan Hu is the 2020 J.E Grizzle Distinguished Alumni Awardee. The Department of Biostatistics is excited to welcome back Dr. Hu! She obtained her doctoral degree from UNC in biostatistics in... Read more »

Greenberg Lectures: Large-Scale Hypothesis Testing for Causal Mediation Effects with Applications in Genome-wide Epigenetic Studies

The 2021 Bernard G. Greenberg Distinguished Lecture Series Featuring Professor Xihong Lin, Harvard University Lecture 2: May 20, 3-4 p.m. Large-Scale Hypothesis Testing for Causal Mediation Effects with Applications in Genome-wide Epigenetic Studies In genome-wide epigenetic studies, it is of great scientific interest to assess whether the effect of exposure on a clinical outcome is... Read more »

Greenberg Lectures: Regression Models for COVID-19 Epidemic Dynamics with Incomplete Data

The 2021 Bernard G. Greenberg Distinguished Lecture Series Featuring Professor Xihong Lin, Harvard University Lecture 3: May 21, 10-11 a.m. Regression Models for COVID-19 Epidemic Dynamics with Incomplete Data Modeling infectious disease dynamics has been critical throughout the COVID-19 pandemic. Of particular interest are the incidence, total prevalence, and effective reproductive number (Rt). Estimating these... Read more »