DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework.

DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework. Comput Math Methods Med. 2020;2020:7231205 Authors: Huang PJ, Chang JH, Lin HH, Li YX, Lee CC, Su CT, Li YL, Chang MT, Weng S, Cheng WH, Chiu CH, Tang P Abstract Although sequencing a human genome has become affordable, identifying genetic variants from whole-genome sequence data is still a hurdle for researchers without adequate computing equipment or bioinformatics support. GATK is a gold standard method for the identification of genetic variants and has been widely used in genome projects and population genetic studies for many years. This was until the Google Brain team developed a new method, DeepVariant, which utilizes deep neural networks to construct an image classification model to identify genetic variants. However, the superior accuracy of DeepVariant comes at the cost of computational intensity, largely constraining its applications. Accordingly, we present DeepVariant-on-Spark to optimize resource allocation, enable multi-GPU support, and accelerate the processing of the DeepVariant pipeline. To make DeepVariant-on-Spark more accessible to everyone, we have deployed the DeepVariant-on-Spark to the Google Cloud Platform (GCP). Users can deploy DeepVariant-on-Spark on the GCP following our instruction within 20 minutes and start to analyze at least ten whole-genome sequencing datasets using free credits provided by the GCP. DeepVarai...
Source: Computational and Mathematical Methods in Medicine - Category: Statistics Tags: Comput Math Methods Med Source Type: research