This is a tutorial for Metagenome-Atlas. Metagenome-Atlas is an easy-to-use pipeline for analyzing metagenomic data. It handles all steps from QC, Assembly, Binning, to Annotation.
Usually before starting to install a program I want to make sure that it gives the output I want. Therefore, we start analyzing the output of Metagenome-atlas.
✨ Follow this link to the interactive tutorial.
We prepared an interactive jupyter notebook & Rmarkdown with the code for differential analysis. The goal is to find out which changes are associated with High fat diet induced obesity in mice.
Click on the links below:
If something doesn't work, let us know.
If you want to run this code on your machine.
Download this repo either as zip or with git clone. In the directories Python and R are dedicated scripts to install the necessary packages to run the code.
In this part of the tutorial you will install metagenome-atlas on your system and test it with a small dataset. As real metagenomic assembly can take more than 250GB ram and multiple processors, you would ideally do this directly on a high-performance system, e.g. the cluster of your university. You can install minconda in your home directory if it is not installed on your system.
If you want only do the test dataset, you can do most steps on a normal laptop (Mac or Linux). See also the get started section in the documentation.