Welcome to Chen Group at U Chicago!
Computational and statistical genomics
Our research group develop computational and statistical tools to address the challenges high-throughput genomics technologies have posed for data analysis and interpretation, particularly for data emerging from biomedical studies.
Single cell genomics
Most of our work focuses on accounting for unwanted variation due to technical artifacts from single cell experiments. Completed and ongoing projects include developing methods to:
The paradigm-shifting discoveries in RNA modifications have added RNA to the picture of dynamic regulation of gene expression through reversible chemical modifications. Successful transcriptome wide profiling of RNA modifications can significantly advance the frontier of epitranscriptomics research and associate epitranscriptomic variations with human health and diseases. We are developing methods for the following topics:
The cancer genome is characterized by genetic heterogeneity that is seen across tumor types, among samples of a particular type (inter-tumor heterogeneity) and within an individual tumor (intratumor heterogeneity). Understanding tumor heterogeneity is a prerequisite for personalized tumor diagnosis and treatment. We are developing methods for integrative tumor heterogeneity analysis using both single cell RNA sequencing and bulk tissue DNA sequencing data.
We welcome U Chicago students from the following programs (but not limited to): Human Genetics, GGSB, Statistics, Data Science and Biophysics. Postdoc positions are also available.
- 01/05/19 Xiaoyang came to the lab as the second postdoc joint with Prof. Chuan He in Department of Chemistry.
- 12/18/18 We received an Epitranscriptome Pilot grant from U of Chicago Comprehensive Cancer Center.
- 10/23/18 Our paper with Xiang Zhou Group on scRNA-seq imputation is published on Genome Biology.
- 05/06/18 Qi joined the lab as a summer intern with support from Hodson Fellowship.