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IMAP: Integrated Microbiome Analysis Pipelines: End-to-End Practical User Guides Using Integrated Approaches

4 Data Science & Visualization Tools

The most powerful tools for analyzing and visualizing microbiome data include:

  • R and RStudio
  • R-markdown
  • Python
  • Jupyter notebook

4.1 Installing R Environment

R is open-source software designed for statistical computing, data analysis, and graphics[3]. You can install the R application on your personal computer to work with the R programming language. Follow these steps to download and install R:

  1. Visit https://www.r-project.org/.
  2. On the left side, under ‘Download,’ click on CRAN to access the mirrors. CRAN (Comprehensive R Archive Network) is mirrored on nearly 100 registered servers across almost 50 regions worldwide. Check the CRAN mirror status.
    • Choose a mirror close to your location; R will automatically connect to that server for downloading the package files.
  3. Select a compatible platform to download precompiled binary distributions of the base system, which also includes contributed packages.


4.2 Installing RStudio Environment

RStudio is a free program that functions as an IDE (Integrated Development Environment), seamlessly integrating with R to implement a wide range of analytical functionalities[4]. For effective analysis, it’s essential to install R before proceeding with the installation of RStudio. We will extensively utilize the RStudio IDE, which provides a user-friendly interface. Specifically, we are interested in RStudio Desktop, an open-source desktop application. Follow these steps to install it:

  1. Visit RStudio.
  2. Click on the RStudio Desktop box to access the open-source edition.
  3. Choose your preferred license, whether it’s open source or commercial.
  4. Select the installer that is compatible with your operating system.


Screen shot of RStudio User Interface
Screen shot of RStudio User Interface


4.3 Installing Python

Python can be installed using various methods, with some of the most popular approaches being:

  1. Direct Downloads: Obtain Python directly from the official Python website by downloading the installer for your operating system.

  2. Environment and Package Management Systems: Utilize tools like conda to manage Python environments and install packages. For instance, you can use the following command with conda:

conda config --add channels conda-forge

conda config --set channel_priority strict

conda install python=3.10

4.4 Installing using environment.yml 

name: python
channels:
    - conda-forge
dependencies:
    - python
    - python-abi
conda activate base
mamba env create --name python --file environment.yaml