Xingyi Guo, PhD
Assistant Professor, Department of Medicine, Division of Epidemiology
Our lab is affiliated with Vanderbilt University Medical Center, Departments of Medicine and Bioinformatical Informatics. We have a broad interest in the research of cancer etiology, prevention and precision medicine through developing bioinformatic and statistical approaches and intergraring multi-omics data, with a major goal of identifying genetic susceptibility factors for human cancers.
i) We are applying and developing bioinformatics tools and pipelines to process large multi-omics data, including whole genome sequencing (WGS), whole exome sequencing (WES), RNA-seq, array-based genotype and epigenetic data, as well as metabolomics data. We have established computing platforms via our local university computing resource (Advanced Computing Center for Research & Education, ACCRE) and Amazon Web Services (AWS) to handle population-based sequencing data for identifying genetic variants (i.e. coding and structure variants) and somatic mutations in human cancers.
ii) We are highly interested in developing computational epigenetics (i.e. ChIP-seq and ATAC-seq) and statistical approaches to improve discovery of susceptibility non-coding variants (i.e. regulatory variants) and genes from current study designs of genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS). Dr. Guo received an NIH grant to conduct a large TWAS of colorectal cancer (R37CA227130, PI: Guo X).
iii) We are building statistical models to explore the inter-relationship of somatic alterations in tumor tissues (i.e. tumor mutational budern/mutational signatures/tumor-infiltrating lymphocytes (TILs)) with genetic susceptibility and carcinogens environmental exposures in human cancers.
iv) In order to understand the underlying molecular mechanisms of carcinogenesis, we are conducting cell and molecular biology studies, including in vitro functional assays to investigate the biological functions of genes in cell proliferation, invasion, and clonogenesis.
We are looking for enthusiastic postdoctoral associates to join our group. Candidates should have PhD in bioinformatics, computational biology, biostatistics, genomics, molecular biology or related fields. Please contact the PI, Xingyi Guo, for details.