Advances in sequencing technology have allowed researchers to produce unprecedented amounts of genomic data. However, uniformly analyzing large sequencing data sets remains a tremendous burden. SwiftSeq is a robust workflow for processing both large and small quantities of DNA sequencing analysis and delivers annotated SNV, indel, and structural variant calls.

Once deployed this workflow can be used to understand how mutations, both germline and somatic, contribute to cancer development. Deleterious germline variations set the stage on which somatic mutations act. By analyzing hundreds of terabytes of sequencing data across nearly 10,000 individuals, we've shown that the presence of deleterious germline variants can lead to recurrent somatic alterations and subsequent inactivation of known and putative susceptibility genes. Loss of these novel genes are also associated with unfavorable outcomes, suggesting that they could be used as both susceptibility and prognostic markers.

SwiftSeq is under active development and not yet available for public download.