AWS HPC Blog

Tag: Genomics

How Caris Life Sciences processed 400,000 RNAseq samples in 2.5 days with AWS Batch

How Caris Life Sciences processed 400,000 RNAseq samples in 2.5 days with AWS Batch

In the race to deliver precision medicine, time is of the essence. Caris Life Sciences, a pioneer in this field, leveraged AWS Batch to build a highly scalable solution that processed hundreds of thousands of genomic samples in record time. Discover how they achieved this remarkable feat and the key services that powered their breakthrough.

Leveraging Seqera Platform on AWS Batch for machine learning workflows - Part 1 of 2

Leveraging Seqera Platform on AWS Batch for machine learning workflows – Part 1 of 2

Nextflow is popular workflow framework for genomics pipelines, but did you know you can also use it for machine-learning? ML is already being used for medical imaging, protein folding, drug discovery, and gene editing. In this post, we explain how to build an example Nextflow pipeline that performs ML model-training and inference for image analysis.

Running accurate, comprehensive, and efficient genomics workflows on AWS using Illumina DRAGEN v4.0

In this blog, we provide a walkthrough of running Illumina DRAGEN v4.0 genomic analysis pipelines on AWS, showing accuracy and efficiency, copy number analysis, structural variants, SMN callers, repeat expansion detection, and pharmacogenomics insights for complex genes. We also highlight some benchmarking results for runtime, cost, and concordance from the Illumina DRAGEN DNA sequencing pipeline.

Cost-effective and accurate genomics analysis with Sentieon on AWS

In this blog post, we benchmark the performance of Sentieon’s DNAseq and DNAscope pipelines using publicly available genomics datasets on AWS. You will gain an understanding of the runtime, cost, and accuracy performance of these germline variant calling pipelines across a wide range of Amazon EC2 instances.