News

Correcting Batch Effects in Microbiome Data

Batch Effects in 16S Datasets Complicate Cross-Study Comparisons

High-throughput data generation platforms, like mass-spectrometry, microarrays, and second-generation sequencing are susceptible to batch effects due to run-to-run variation in reagents, equipment, protocols, or personnel. Currently, batch correction methods are not commonly applied to microbiome sequencing datasets. In this paper, we compare different batch-correction methods applied to microbiome case-control studies. We introduce a model-free normalization procedure where features (i.e. bacterial taxa) in case samples are converted to percentiles of the equivalent features in control samples within a study prior to pooling data across studies. We look at how this percentile-normalization method compares to traditional meta-analysis methods for combining independent p-values and to limma and ComBat, widely used batch-correction models developed for RNA microarray data. Overall, we show that percentile-normalization is a simple, non-parametric approach for correcting batch effects and improving sensitivity in case-control meta-analyses.

You can read more about this work in our recent PloS Computational Biology article.

The code for running percentile normalization is available on github and can be applied as a QIIME2 plugin.

Related Articles

  • ISB's Dr. Sean Gibbons on the importance of the human microbiome

    “This new organ that we’re coming to recognize as the microbiome is part and parcel to the functionality of the whole system, and if it breaks down, if it starts to fall apart, we start to get sick,” said Dr. Sean Gibbons, ISB’s newest faculty member, in a WGBH Forum Network presentation.

    Read More
  • Dr. Sean Gibbons joins ISB faculty as WRF Distinguished Investigator

    Dr. Sean Gibbons has joined ISB as our newest faculty member. Gibbons’ new position brings a number of changes, including relocating to the Pacific Northwest from the Northeast. Read on for a Q&A with Gibbons that sheds light on his research career to date, areas of study and even a hidden talent.

    Read More
  • Christian Diener Joins the Lab

    Christian Diener will join the Institute for Systems Biology as the Washington Research Foundation Distinguished Postdoctoral Fellow in the Gibbons Lab. Christian is a computational biologist who has worked extensively on yeast systems biology and has recently moved into studying the human microbiome. He completed his PhD in systems biology at the Max Plank Institute for Molecular Genetics and is currently working at the National Institute for Genome Medicine in…

    Read More