DHVI Quantitative Research Division (QRD) (Co-Directors: Kevin Wiehe, PhD and Wes Rountree, MPH)
Biostatistics Support: The QRD supports DHVI investigators and their collaborators in study design, data collection and management, data analysis, and power calculations. The QRD works with Principal Investigators and laboratories to create permanent datasets in SAS for storage on a secure server. For larger projects, the QRD works with external contractors to develop systems databases (e.g., the DHVI Laboratory Assay System for CHAVI and CHAVI-ID, the EQAPOL and IQA Web-Based System). The QRD also provides statistical support for clinical studies at DHVI including the CDC CISA program where they manage statistical analyses and the NIH DMID VTEU program where they consult on study design and sample size/power calculations. The QRD collaborates with Principal Investigators to prepare individual and multi-investigator grants, as well as assists in preparing manuscripts for submission to a wide-range of peer-reviewed journals. The QRD biostatistics team has a wide variety of statistical expertise ranging from non-parametric and categorical analysis, epidemiologic methods, general and generalized linear models, structural equation models, and finite mixture models. The QRD biostatistics team has expertise using SAS and R for data management and the creation of tables and figures.
Computational Biology Support: The QRD supports the wide array of computational biology and bioinformatics needs of DHVI investigators. The QRD has a central focus in the area of computational immunology and assists investigators with immunogenetic classification, clonal clustering, clonal genealogy reconstruction, immunoglobulin allelic discovery, and high-throughput antibody repertoire sequencing data analyses. The team also is experienced in performing analysis with a multitude of state-of-the-art bioinformatics techniques and software and is fully-capable of delivering custom bioinformatics solutions including analysis pipeline building. The QRD is well-versed in applying computational genomics techniques with a particular strength in next-generation sequencing approaches for genomic sequencing, RNA-Seq, and single-cell transcriptomics. In addition, the QRD computational biology team offers computational structural biology services and helps DHVI investigators with molecular visualization, antibody structural modeling, antibody-antigen complex modeling, computational immunogen design, computational mutagenesis, in silico antibody affinity improvement, and molecular dynamics simulation. To meet the computationally intensive demands of computational biology analyses which often involve very large datasets, the QRD Computational Biology team is highly proficient in performing analyses in a high performance computing environment utilizing Duke University’s premier supercomputing facility, the Duke Computer Cluster.