About SwiftSeq

For decades, researchers and clinicians have envisioned genetic information playing an inevitable — and significant — role in medical practices. Decreasing sequencing costs and continuous technological improvements now allow us rapidly characterize individuals’ genetic variation, facilitating massive genomic studies and bringing precision medicine closer to actualization. However, the subsequent influx of data increases the cost and complexity of downstream analyses. Substantial hardware resources (CPU, memory, disk space, etc.) are necessary but not sufficient to leverage these data streams. Sophisticated software solutions are required to harness the scientific and clinical opportunities enabled by contemporary sequencing technologies — particularly at scale. To this end, we have developed SwiftSeq, a flexible, portable, and intuitive workflow infrastructure for the analysis of exomes, genomes, or custom capture panels. By design, this approach allows even those with limited programmatic experience to conduct small- and large-scale genomic analyses.

Swiftseq:
  1. Is powered by the parallel scripting language Swift.
  2. Uses scatter-gather parallelism to reduce analysis run time by up to 8x.
  3. Efficiently utilizes compute resources by packing tasks on workers.
  4. Has a proven track record of scalability.
  5. Workflow execution is fault tolerant and can be halted/restarted.
  6. Natively supports germline and tumor-normal pair variant calling.
  7. Allows users to specify algorithms and parameters via a graphical interface.
  8. Can run on laptops/desktops, clusters, high-performance computing architectures, and cloud resources — both commercial and private.
  9. Is open source.