Educational Resources for for Amplicon Metagenomics


  1. mothur and QIIME


  1. CoDaSeq workshop
    • Description: The intention of this workshop is to give participants a background in Compositional Data Analysis (CoDa) for transcription studies. At the end of the workshop you will have been introduced to CoDa, why you’d use CoDa, and gain hands-on experience using CoDa analysis in R.
    • Link:
  2. Microbiota Analysis in R [workshop/tutorial]
    • Description: The goal of this tutorial is to demonstrate basic analyses of microbiota data to determine if and how communities differ by variables of interest. In general, this pipeline can be used for any microbiota data set that has been clustered into operational taxonomic units (OTUs).
    • Link:


  1. Microbiota Procesing in mothur: standard operating procedure (SOP)
    • Description: The goal of this tutorial is to demonstrate standard operating procedures (SOP) for processing amplicon data that are generated using Illumina’s MiSeq platform with paired end reads.
    • Link:
  2. 16S Metagenomic Analysis Tutorial
  3. An Introduction to Applied Bioinformatics[OnlineBook]
    • Description: An Introduction to Applied Bioinformatics (or IAB) is a free, open source interactive text that introduces readers to core concepts of bioinformatics in the context of their implementation and application.
    • Link: Focus mainly on following chapters
      1. Phylogenetic reconstruction
  4. Microbiome data analysis
  5. QIIME2 Tutorials

    1. QIIME2 Glossary
    2. Overview of QIIME2 Plugin Workflows
    3. Microbiome Analysis with QIIME2: A Hands-On Tutorial[Presentation]
    4. “Moving Pictures” tutorial [VeryNiceTutorial!]
      • Description: In this tutorial you’ll use QIIME 2 to perform an analysis of human microbiome samples from two individuals at four body sites at five timepoints, the first of which immediately followed antibiotic usage.
      • Link:
    5. QIIME2 workflow
  6. Amplicon Metagenomics
  7. Taxonomy from species name in R


Guide to improve Python performance.

9 minute read

The primary objective of this guide is to summarize all of the popular approaches for boosting the execution speed of your Python code.

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