Project

Can You Transplant It?

5 completions
~ 19 hours
New

Immerse yourself into the world of metagenomics by using QIIME 2 to study the outcomes of the FMT procedure. In this project, you will not only learn about the main analysis steps but also study various metrics, which are used to describe microbiomes.

Provided by

Edvancium Edvancium

About

You are a bioinformatician at a clinic division, which targets gut diseases. Your division aims to find a way to cure the recurrent Clostridium difficile infection, which often affects people after using antibiotic medications. The C. difficile infection typically impacts the colon, causing a range of symptoms, including diarrhea, high temperature, and gut ache. In the worst cases, it can cause life-long damage to the colon. To treat the recurrent infection, the doctors in your division have decided to try fecal microbiota transplantation (FMT) [1]. Your task is to determine whether the FMT has helped the patients!

[1] Khanna, S., Vazquez-Baeza, Y., González, A. et al. Changes in microbial ecology after fecal microbiota transplantation for recurrent C. difficile infection affected by underlying inflammatory bowel disease. Microbiome 5, 55 (2017). 

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Training project

This project allows you to practice and strengthen your coding skills, helping you get ready for more advanced tasks ahead.

What you'll learn

Once you choose a project, we'll provide you with a study plan that includes all the necessary topics from your course to get it built. Here’s what awaits you:
Use the SRA website to download the data.
Install QIIME 2 and import the data into QIIME 2 artifacts.
Perform data quality analysis using QIIME 2 inbuilt methods.
Perform data denoising and feature table creation with QIIME 2 plugin DADA2.
Merge the resulting datasets together to perform further analysis. Use the resulting sequences to construct multiple sequence alignment and build a phylogenetic tree. Based on it, run a simple command to generate a ton of unknown metrics.
Use richness and evenness metrics to describe the communities within each sample based on Alpha diversity.
Use Beta diversity metrics to definitely say whether the FMT has helped the patients with Clostridium difficile infection!