Leigh, R.J. and Murphy, R.A. and Walsh, F. (2021) statSuma: automated selection and performance of statistical comparisons for microbiome studies. Cold Spring Harbor perspectives in medicine. ISSN 2157-1422

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Abstract

There is a reproducibility crisis in scientific studies. Some of these crises arise from incorrect application of statistical tests to data that follow inappropriate distributions, have inconsistent equivariance, or have very small sample sizes. As determining which test is most appropriate for all data in a multi-categorical study (such as comparing taxa between sites in microbiome studies), we present statsSuma, an interactive Python notebook (which can be run from any desktop computer using the Google Colaboratory web service) and does not require a user to have any programming experience. This software assesses underlying data structures in a given dataset to advise what pairwise or listwise statistical procedure would be best suited for all data. As some users may be interested in further mining specific trends, statSuma performs 5 different two-tailed pairwise tests (Student’s t-test, Welch’s t-test, Mann-Whitney U-test, Brunner-Munzel test, and a pairwise Kruskal-Wallis H-test) and advises the best test for each comparison. This software also advises whether ANOVA or a multi-categorical Kruskal-Wallis H-test is most appropriate for a given dataset and performs both procedures. A data distribution-vs-Gaussian distribution plot is produced for each taxon at each site and a variance plot between all combinations of 2 taxa at each site are produced so Gaussian tests and variance tests can be visually confirmed alongside associated statistical determinants.

Item Type:	Article
Additional Information:	statSuma: automated selection and performance of statistical comparisons for microbiome studies R.J. Leigh, R.A. Murphy, F. Walsh bioRxiv 2021.06.15.448299; doi: https://doi.org/10.1101/2021.06.15.448299
Keywords:	multi-categorical study; statsSuma;
Academic Unit:	Faculty of Science and Engineering > Biology Faculty of Science and Engineering > Research Institutes > Human Health Institute
Item ID:	17328
Identification Number:	https://doi.org/10.1101/2021.06.15.448299
Depositing User:	Dr Robert Leigh
Date Deposited:	15 Jun 2023 14:21
Journal or Publication Title:	Cold Spring Harbor perspectives in medicine
Publisher:	CSHL press
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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