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Assessing and removing the effect of unwanted technical variations in microbiome data
Muhamad Fachrul1,2, Guillaume Méric1,3, Michael Inouye1,2,4,5,6,7
1Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia.
Scientific Reports
|December 23, 2022
Summary
Technical variations in microbiome studies can cause irreproducible results. This study identifies storage and freeze-thaw cycles as key sources, demonstrating how computational methods like RUV-III-NB can minimize their impact on microbial data.
Area of Science:
- Microbiome research
- Metagenomics
- Bioinformatics
Background:
- Microbiome studies face challenges with reproducibility due to technical variations.
- Unaccounted technical variations can obscure true biological signals and lead to incorrect conclusions.
Purpose of the Study:
- To identify major sources of technical variation in microbiome data.
- To evaluate in-silico methods for minimizing the impact of these variations.
- To improve the reliability of microbiome data analysis.
Main Methods:
- Analysis of 184 pig faecal metagenomes with introduced technical and biological variations.
- Application of the Removing Unwanted Variations-III-Negative Binomial (RUV-III-NB) method.
- Benchmarking of multiple variation correction methods (ComBat, ComBat-seq, RUVg, RUVs, RUV-III-NB).
Main Results:
- Storage conditions and freeze-thaw cycles identified as significant sources of unwanted variation.
- Technical variations impact microbial taxa non-uniformly, affecting specific classes like Bacteroidia.
- RUV-III-NB demonstrated robust performance in removing unwanted variations compared to other methods.
Conclusions:
- Careful experimental design considering technical confounders is crucial for microbiome studies.
- Incorporating technical replicates is essential for effective computational removal of unwanted variations.
- RUV-III-NB offers a reliable approach for correcting technical variations in metagenomic data.
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