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Processing 16S data

An informal primer about 16S rRNA amplicon data

This document is not a tutorial. If you desperately need to turn some raw data into OTU tables in the next 10 hours, don’t read this document. If you want to know something more principled about how to turn fastq's into OTU tables, read on.

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About

About

About the Book

My goal for this document is to help you understand the theory behind 16S data processing. I want you to be able to do the analysis that makes the most sense for you. There are pipelines that make data analysis easy and simple. I aim to show you how the sausage is made. The entire data collection process, from sample collection to OTU calling, is discussed, with particular emphasis on preparing raw sequencing data for OTU calling and on selection of OTU calling methodology.

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About the Author

Scott W. Olesen

Scott earned his PhD student in Biological Engineering at MIT in 2016. His graduate work focused on creating conceptual and quantitative tools for analyzing microbiome data.

Contents

Table of Contents

  •  
    • Foreword
      • Where this document came from
      • What this document is for
      • Who this document is for
      • What this document is not
    • Where 16S data comes from
      • The 16S gene
      • Getting DNA from a sample
      • Amplifying the gene
      • The amplified DNA is not exactly like the original DNA
      • Multiplexing helps evaluate contamination (or other weirdness)
      • Sequencing
    • Data processing theory
      • Raw data and metadata
      • Overview of the processing pipeline
      • Details of each step
    • OTU-calling theory
      • An abridged history of the OTU
      • Why call OTUs?
      • OTU calling is not the same as lineage assignment
      • Common and uncommon OTU-calling methods
    • Practice
      • File formats
      • Existing tools
      • Your own tools
      • Some early challenges
    • Second opinions
      • usearch documentation
      • Pipeline tutorials
  • Notes

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