Speaker Profile

Stacey Gabriel

Biography

Under Gabriel’s guidance, the Genomics Platform explores, validates, optimizes, and implements new technologies, methods, and analysis tools to meet the needs of the Broad community. Gabriel and the members of her team are committed to pushing the boundaries of the genomic frontier through the application of operational excellence, advanced process design, data analysis and visualization, and technology development capabilities. In addition to her activities with the Genomics Platform, Gabriel’s research interests lie in using genomic techniques to understand the genetic component of common disease. She has represented the Broad in many large national projects, including providing foundational research for the International HapMap Project; serving on the steering committee for the 1000 Genomes Project, as well as co-chairing the project’s production group; serving on the steering committee for The Cancer Genome Atlas; serving as principal investigator on the National Heart, Lung and Blood Institute’s Exome Sequencing Project; and co-principal investigator (with Eric Lander) of the National Human Genome Research Institute’s large-scale sequencing center at the Broad Institute. She has also served as principal investigator on eight NIH grants, totaling over $200 M, related to large-scale genotyping, sequence production, and analysis.

Talk

To the Cloud(s): Keeping up with DNA Sequencing
Recent advances in genomics technology have created vast opportunity in the breadth (scale of data collection, type of nucleic acid, type of event) and the resolution (rare somatic mutations, single cells, cfDNA) at which human biology can be studied. In particular, implementation of the HiSeqX platform has opened the door to human whole genome sequencing in an unprecedented way, enabling projects that would now have been undertaken previously and setting the stage for bold new directions at the population scale. Along with this we experience a divergence in the growth of DNA sequencing versus cost and scalability of compute as well as ease of data sharing and aggregation. In order to keep up with sequencing at population scale we require scalable, efficient, and cost effective analysis approaches to eliminate computation as the gating factor in the progress of scientific discovery. We will discuss challenges and findings from our experience, and an approach to empower other researchers to leverage our cloud-based best practice analysis pipelines capable of processing a whole genome every 4 minutes.