Making Sense of MicrobesMetagenomic Analysis Workflow

CSIRO COMPUTATIONAL INFORMATICS

Jack Simpson

10 Februrary 2014

Cells in the human body

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Microbial:100 trillion

Human10 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

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OTU counts

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Samples

Metagenomics workflow

• Three areas I found interesting over the summer

• Background of the data

• Working with count data

• Finding associations

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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

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Working with count data

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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

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Heatmap of all counts

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Beware hidden complexity

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Heatmap of grouped counts

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Zoom in on the heatmap

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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

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Gut log compositional and log raw data

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Gut log compositional & clr compositional

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Finding associations

• Warning: compositional data!

• Be careful with correlation

• Fractions are not independent == negative correlation

• What can be done?

• Proportionality

Presentation title | Presenter name16 |

Summary

• Metagenomic data background

• Processing our data

• Looking for associations the right way

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Thank-you!

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