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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
Published on: October 15, 2019
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Enhancing diversity analysis by repeatedly rarefying next generation sequencing data describing microbial communities
Ellen S Cameron1, Philip J Schmidt2, Benjamin J-M Tremblay1
1Department of Biology, University of Waterloo, 200 University Ave. W, Waterloo, ON, N2L 3G1, Canada.
Scientific Reports
|November 17, 2021
Summary
Repeated rarefying normalizes amplicon sequencing data for microbial community analysis. This method ensures proportionate sequence representation and quantifies variation introduced by library size normalization, improving water quality assessments.
Area of Science:
- Environmental microbiology
- Bioinformatics
- Water quality assessment
Background:
- Amplicon sequencing is a powerful tool for analyzing microbial communities in environmental DNA, overcoming limitations of traditional methods.
- It is crucial for monitoring water resources, detecting shifts due to disturbances, and identifying potential health risks like toxic cyanobacteria or pathogens.
- Amplicon sequencing data requires normalization due to varying library sizes, which can obscure biological variation and hinder diversity comparisons.
Purpose of the Study:
- To propose repeated rarefying as a robust method for normalizing library sizes in amplicon sequencing data.
- To demonstrate how this method ensures proportionate representation of all observed sequences.
- To characterize the random variation introduced by rarefying to a common library size.
Main Methods:
- Utilizing repeated rarefying to subsample sequences from diverse library sizes to a uniform, smaller library size.
- Applying this probabilistic approach to reflect the nature of amplicon sequencing data generation.
- Evaluating the impact of this normalization on diversity analysis results through graphical representation.
Main Results:
- Repeated rarefying provides proportionate representation of all observed sequences across samples.
- It allows for the characterization of random variation introduced by subsampling to a common library size.
- This method offers a more statistically grounded approach to library size normalization for diversity analyses.
Conclusions:
- Repeated rarefying is a statistically sound and practical method for normalizing amplicon sequencing data.
- This normalization technique enhances the reliability of microbial community diversity analyses in water resources management.
- The approach facilitates a clearer understanding of ecosystem health by accurately reflecting microbial community structures.
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