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Di Wu

Assistant Professor, Department of Biostatistics
Assistant Professor, UNC School of Dentistry
UNC Gillings School of Global Public Health
UNC-Chapel Hill
Cancer Genetics

Area of Interest

My goal, via genomic data analysis and integration, is to better understand disease mechanism and to improve people’s health. I am trained as a biostatistician working in the bioinformatics field. My research interest and contributions are in both the methodology development and the application of these methods (among other methods) in cancer related research. I have extensive experience to work with biologists, clinicians including continuous collaboration with oncologists, and geneticists.  I also develop sophisticated tools to solve new data problems in biomedical research. Right now my main focuses are cancer genomics, microbiome metagenomics/metatranscriptomics, and single cell RNAseq (scRNAseq) data.

I have developed novel statistical methods for genomics data analysis that include gene set analysis (ROAST, CAMERA, and a method for time course data)  and miRNA normalization in cancer samples. These methods have been highly cited by many transcriptome studies (including cancer studies) for pathway analysis and relating datasets by similar expression pattern in signature gene sets.

My PhD work about breast cancer was to find the cell of origin of different breast cancer molecular subtypes (data from Chuck Perou) by pathway analysis and gene sets tests across multiple datasets. As a postdoc, I developed the bioinformatics data integration framework of drug discovery for lung squamous cell carcinoma (SqCC) (data from Neil Hayes) and a drug repurposing framework for autoimmune diseases based on GWAS risk SNPs and public drug target database. In the SqCC study, I have characterized the signature genes of SqCC, related them to cell lines, and identified the corresponding potentially effective drugs. Other cancer types I have worked on include gastric cancer, skin cancer, prostate cancer and oral cancer. The GWAS based drug repurposing project can be extended to “Genomic data based Cancer-subtype specific drug repurposing particularly through statistical causal pathway analysis.

At UNC, I have collaborated with Cyrus Vazziri in the School of Medicine on the relation between DNA repair pathways and cancer mechanism, by analyzing local mouse WES data and integrating TCGA data, potentially applied in HPV-negative oral cancer studies. Meanwhile, my group is also developing various statistical methods in scRNAseq pathway analysis (applied for understanding cancer initiation/progression, and characterizing HIV infected mouse), differential expression analysis and clustering analysis, as well as methods for metagenomics data and microbial omics data integration particularly when DNAseq, RNAseq, and metabolome data are all available. Connection between dental Electronic Patient Records (EPR) and their Electronic Medical Records (EMR) is current under investigation in my group for their relation to prediction of head and neck cancer.

Honors and Awards

  • Early Career Overseas Fellowship, Australian National Health and Medical Research Council, 2011

Find publications on PubMed