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AACR19 Poster - Somatic Analysis In the Cloud - TAG

Junko Tsuji, Andrew Hollinger, Alyssa MacBeth, Brian R. Grander, Micah Rickles-Young, Tera Bowers, Carrie Cibulskis, Niall Lennon. Broad Institute of MIT and Harvard, Cambridge, MA 

Abstract
With advances in high-throughput sequencing technologies and analytical tools, genomic analysis of tumors has led to the identification of various important somatic mutations that shed light on diagnosis, prevention, and treatment for cancer. However, detecting somatic variants is not a trivial task in terms of the technical aspects (e.g. filtering germline events and removing a variety of noises in tumor samples) and computational resources to handle large-scale cohort analysis. There is also a demand for maintaining stable software versions and the workflows for studies over extended periods of time, that need consistency and traceability, such as clinical trials. We introduce here, the Translational Analysis Group (TAG), a team which deploys, validates, and conducts scalable analytical workflows in a secure, cloud-based environment. We maintain 29 well-tested workflows with best practice methods and ample resources for both somatic and germline analysis. Our cloud platform, FireCloud, enables us to run workflows at any scale. Since May 2017, our team has performed nearly 10,000 analyses for mutation detection (SNV, InDel, CNV, and SV) and cohort analysis on tumor samples and cell-free DNA samples. TAG offers a range of options for somatic and germline variant detection, from legacy pipelines through recently validated contemporary pipelines to allow for continuity across long running projects.
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