Emmanuel L P Dumont1, Benjamin Tycko1,2,3, Catherine Do1. 1. Hackensack-Meridian Health Center for Discovery and Innovation, Nutley, NJ 07110, USA. 2. Hackensack-Meridian Health School of Medicine at Seton Hall University, Nutley, NJ 07110, USA. 3. Lombardi Comprehensive Cancer, Center Georgetown University, Washington, DC 20007, USA.
Abstract
SUMMARY: Methods for quantifying the imbalance in CpG methylation between alleles genome-wide have been described but their algorithmic time complexity is quadratic and their practical use requires painstaking attention to infrastructure choice, implementation and execution. To solve this problem, we developed CloudASM, a scalable, ultra-efficient, turn-key, portable pipeline on Google Cloud Platform (GCP) that uses a novel pipeline manager and GCP's serverless enterprise data warehouse. AVAILABILITY AND IMPLEMENTATION: CloudASM is freely available in the GitHub repository https://github.com/TyckoLab/CloudASM and a sample dataset and its results are also freely available at https://console.cloud.google.com/storage/browser/cloudasm. CONTACT: emmanuel.dumont@hmh-cdi.org.
SUMMARY: Methods for quantifying the imbalance in CpG methylation between alleles genome-wide have been described but their algorithmic time complexity is quadratic and their practical use requires painstaking attention to infrastructure choice, implementation and execution. To solve this problem, we developed CloudASM, a scalable, ultra-efficient, turn-key, portable pipeline on Google Cloud Platform (GCP) that uses a novel pipeline manager and GCP's serverless enterprise data warehouse. AVAILABILITY AND IMPLEMENTATION: CloudASM is freely available in the GitHub repository https://github.com/TyckoLab/CloudASM and a sample dataset and its results are also freely available at https://console.cloud.google.com/storage/browser/cloudasm. CONTACT: emmanuel.dumont@hmh-cdi.org.
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