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R Shiny application accompanying the paper (unpublished) Evaluation of Computational Methods for Human Microbiome Analysis Using Simulated Data

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Evaluation of Computational Methods for Human Microbiome Analysis Using Simulated Data

This is the repository for the simulated data, code, and visualization (Shiny App) presented in the paper Evaluation of Computational Methods for Human Microbiome Analysis Using Simulated Data (Miossec et al., 2020).
Code written by Sandro Valenzuela.

DATA

To download the simulated data, please click on the following links according to the number of species simulated you wish to try:

  • Data simulating 10 species from the Human Oral Microbiome Database here.
  • Data simulating 100 species from the Human Oral Microbiome Database here.
  • Data simulating 426 species from the Human Oral Microbiome Database here.

CODE

To streamline data generation and analyses, we wrote four modules that work sequentially to from simulation, execution, parsing, and analysis. Check out the following repositories for each step:

  • To simulate reads as we did in the study here.

  • To execute the methods and pipelines benchmarked in the study here.

  • To parse the results from the different software pipelines here.

  • and to carry out statistical analyses here.

VISUALIZATION in dedicated Shiny App

R Shiny app interface

To run the app, simply download the R scripts in this folder as well as data and modules. Make sure R is installed on your machine (https://www.r-project.org/). For a slick R dev interface, we recommend using Rstudio (https://www.rstudio.com/)

Before attempting to run the app, make sure that the following required packages are installed:

  • shiny
  • shinythemes
  • stringr
  • ggplot2
  • reshape2
  • phyloseq
  • plyr

The Phyloseq package should be downloaded from bioconductor following the instructions given at: https://bioconductor.org/packages/release/bioc/html/phyloseq.html.

All other packages can be downloaded using the R command: install.packages(nameofthepackage).

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R Shiny application accompanying the paper (unpublished) Evaluation of Computational Methods for Human Microbiome Analysis Using Simulated Data

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