curatedMetagenomicDataAnalyses

This repository provides biologically relevant analyses using the curatedMetagenomicData package, both using R/Bioconductor and using Python. You can run both R and Python analyses locally in the provided Docker container, or on the Cloud for free.

Running in the Cloud (free)

A machine with all dependencies, code from this repository, and Jupyterlab (with R and Python3) and RStudio running is available at http://app.orchestra.cancerdatasci.org/ (search for the Curated Metagenomic Analyses workshop). You can use these machines for up to 8 hours at a time.

Running locally using Docker

Requirements

You need Docker.

Getting Started

First build the image:

docker build -t "waldronlab/curatedmetagenomicanalyses" .

Then run a container based on the image with your password:

docker run -d -p 80:8888 --name cma \
  waldronlab/curatedmetagenomicanalyses

Visit localhost in your browser.

Running locally without Docker

Start with an installation of the current version of Bioconductor (see https://bioconductor.org/install/). Older versions probably will not work. Installation directly from GitHub requires first installing the remotes package, then:

BiocManager::install("waldronlab/curatedMetagenomicDataAnalyses", dependencies = TRUE)

Analyses

R Vignettes

• Create datasets for machine learning
• Exploration of the liver cirrhosis dataset
• Select all colorectal cancer patients and create a cohort table, calculate prevalence of all species found in their stool microbiomes and create a dynamic searchable html table
• Meta-analysis of age-related microbial species using cMD3
• Meta-analysis of sex-related microbial species using cMD3
• NUI Galway Metagenomics Workshop

Python Notebooks

• Sex-related differences in the human microbiome using cMD3 and Python3

Supplementary Materials

• Installing Python dependencies in Linux (Python notebook)