DENNIS HAZELETT LABORATORY
Originally trained as a geneticist in the field of developmental biology, I have a broad background in both experimental and computational biology. I rely on a systems-biology approach involving the analysis and synthesis of next-generation sequencing data. My most recent contributions are highlighted by efforts to annotate and draw inference from the functional consequences of genetic associations from genome-wide association studies (GWAS) for prostate cancer, Hodgkins lymphoma and ovarian cancers. Toward this goal, I integrated GWAS and next-generation sequencing data from my collaborators with public datasets such as1000 genomes and the Encyclopedia of DNA elements (ENCODE) to infer new diseases variants outside of transcribed sequences. I have recently begun independent efforts as a principle investigator at Cedars-Sinai Medical Center, using novel approaches to achieve a greater understanding of the relationship between the regulatory code and genetic disease variants.
Research Bioinformatician II
I began my career doing bioinformatics analysis of GWAS data as part of the U19 GAME-ON consortium at USC. Since then, I have focused on the functional consequences of non-protein coding risk regions within the context of many complex diseases. To this end, we developed a software program called FunciSNP, which is an R/Bioconductor tool integrating functional non-coding datasets with genetic association studies to identify candidate regulatory SNPs (Coetzeeet al., 2012). I have worked on analyzing and interpretation of large genomic datasets, including next-generation sequencing from internal collaborations and downloaded from public datasets such as 1000 genomes, The Encyclopedia of DNA Elements (ENCODE), NIH Epigenomics Roadmap, and The Cancer Genome Atlas. At Cedars-Sinai, I am working with Dr. Ben Berman and Dr. Dennis Hazelett to develop automation tools for analysis and functional annotation of genetic variants from large genome and epigenome sequencing projects. I am also continuing my development of novel algorithms for the analysis of gene regulatory sequences