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Area of Science:

  • Bioinformatics and Computational Biology
  • Cloud Computing in Scientific Research

Background:

  • Cloud computing platforms offer scalable resources for scientific computation.
  • Scientists require accessible tools for complex data analysis, such as metagenomics.

Purpose of the Study:

  • To provide a protocol for deploying a virtual machine on Microsoft Azure.
  • To configure an environment for metagenomics analysis using QIIME toolkit.

Main Methods:

  • Deployment of an Ubuntu Linux Virtual Machine on Microsoft Azure.
  • Installation and configuration of Miniconda Python, Jupyter Lab, and QIIME toolkit.
  • Setting up web browser access for the Jupyter Lab server.

Main Results:

  • A functional virtual machine environment for metagenomics analysis is established.
  • The configured system allows for accessible execution of QIIME toolkit pipelines.
  • Rapid prototyping and deployment of computational experiment platforms are facilitated.

Conclusions:

  • Microsoft Azure provides a viable platform for deploying bioinformatics analysis tools.
  • This protocol simplifies the setup of cloud-based computational environments for researchers.
  • The described setup enhances accessibility and efficiency in metagenomics data analysis.