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Unprecedented data volumes and pressure on turnaround time driven by commercial applications require bioinformatics solutions to evolve to meed these new demands. New compute paradigms and cloud-based IT solutions enable this transition. Here I present two solution capable of meeting these demands for genomic variant analysis, VariantSpark, as well as genome engineering applications, GT-Scan2.
VariantSpark classifies 3000 individuals with 80 Million genomic variants each in under 30 minutes. This Hadoop/Spark solution for machine learning application on genomic data is hence capable to scale up to population size cohorts.
GT-Scan2, identifies CRISPR target sites by minimizing off-target effects and maximizing on-target efficiency. This optimization is powered by AWS Lambda functions, which offer an “always-on” web service that can instantaneously recruit enough compute resources keep runtime stable even for queries with several thousand of potential target sites.