DirtyGenes: testing for significant changes in gene or bacterial population compositions from a small number of samples

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Shaw, L.M. ORCID: 0000-0002-0832-964X, Blanchard, A. ORCID: 0000-0001-6991-7210, Chen, Q., An, X., Totemeyer, S., Zhu, Y.-G. and Stekel, D.J., 2019. DirtyGenes: testing for significant changes in gene or bacterial population compositions from a small number of samples. Scientific Reports, 9: 2373. ISSN 2045-2322

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Official URL: https://doi.org/10.1038/s41598-019-38873-4

Abstract

High throughput genomics technologies are applied widely to microbiomes in humans, animals, soil and water, to detect changes in bacterial communities or the genes they carry, between different environments or treatments. We describe a method to test the statistical significance of differences in bacterial population or gene composition, applicable to metagenomic or quantitative polymerase chain reaction data. Our method goes beyond previous published work in being universally most powerful, thus better able to detect statistically significant differences, and through being more reliable for smaller sample sizes. It can also be used for experimental design, to estimate how many samples to use in future experiments, again with the advantage of being universally most powerful. We present three example analyses in the area of antimicrobial resistance. The first is to published data on bacterial communities and antimicrobial resistance genes (ARGs) in the environment; we show that there are significant changes in both ARG and community composition. The second is to new data on seasonality in bacterial communities and ARGs in hooves from four sheep. While the observed differences are not significant, we show that a minimum group size of eight sheep would provide sufficient power to observe significance of similar changes in further experiments. The third is to published data on bacterial communities surrounding rice crops. This is a much larger data set and is used to verify the new method. Our method has broad uses for statistical testing and experimental design in research on changing microbiomes, including studies on antimicrobial resistance.

Item Type:

Journal article

Publication Title:

Scientific Reports

Creators:

Shaw, L.M., Blanchard, A., Chen, Q., An, X., Totemeyer, S., Zhu, Y.-G. and Stekel, D.J.

Publisher:

Nature Publishing Group

Date:

20 February 2019

Volume:

ISSN:

2045-2322

Identifiers:

Number	Type
10.1038/s41598-019-38873-4	DOI

Rights:

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Divisions:

Schools > School of Science and Technology

Record created by:

Jonathan Gallacher

Date Added:

16 Jan 2019 14:15

Last Modified:

01 Mar 2019 15:18

URI:

https://irep.ntu.ac.uk/id/eprint/35577