Making Sense of Microbes - Jack Simpson

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Information about Making Sense of Microbes - Jack Simpson

Published on March 5, 2014

Author: AustralianBioinformatics



Metagenomic Analysis Workflow

Making Sense of Microbes Metagenomic Analysis Workflow Jack Simpson 10 Februrary 2014 CSIRO COMPUTATIONAL INFORMATICS

Cells in the human body Microbial: 100 trillion 2 | Jack Simpson Human 10 trillion

Human Microbiome Project • Investigate impact on human health • ~ 240 healthy individuals • 18 microbial habitats (e.g. airways) • > 5000 samples • Taxonomic marker: 16S rRNA gene 3 | Jack Simpson

OTU counts Samples 4 | Jack Simpson

Metagenomics workflow • Three areas I found interesting over the summer • Background of the data • Working with count data • Finding associations 5 | Jack Simpson

Where does metagenomic data start? • Where did our counts and OTUs come from? • Count data is not raw data: many processing decisions • 16S rRNA gene resolution and primers • Multiple variable regions • Lab protocols and comparing projects • Biological data starts in the real world 6 | Jack Simpson

Working with count data 7 | Jack Simpson

Zeroes: Much Ado About Nothing…? • Does absence of evidence == evidence of absence? • What do we do with zeroes? • Remove or Pseudocounts? • When to remove/replace? • Merged at the class level: visualise and replace zeroes 8 | Jack Simpson

Heatmap of all counts 9 | Jack Simpson

Beware hidden complexity 10 | Jack Simpson

Heatmap of grouped counts 11 | Jack Simpson

Zoom in on the heatmap 12 | Jack Simpson

Processing the Data • OTU count data analysis • Dealt with zeroes • Visualised the data • Normalization and transformation: log or Aitchison’s CLR? • What do different transformations do to the data with different sample numbers? • See artefacts related to discretization and zeroes 13 | Jack Simpson

Gut log compositional and log raw data 14 | Jack Simpson

Gut log compositional & clr compositional 15 | Jack Simpson

Finding associations • Warning: compositional data! • Be careful with correlation • Fractions are not independent == negative correlation • What can be done? • Proportionality 16 | Presentation title | Presenter name

Summary • Metagenomic data background • Processing our data • Looking for associations the right way 17 | Jack Simpson

Thank-you! 18 | Jack Simpson

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