D-MANOVA: fast distance-based multivariate analysis of variance for large-scale microbiome association studies
Abstract Summary PERMANOVA (permutational multivariate analysis of variance based on distances) has been widely used for testing the association between the microbiome and a covariate of interest. Statistical significance is established by permutation, which is computationally intensive for large sa...
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Veröffentlicht in: | Bioinformatics 2021-12, Vol.38 (1), p.286-288 |
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Sprache: | eng |
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Zusammenfassung: | Abstract
Summary
PERMANOVA (permutational multivariate analysis of variance based on distances) has been widely used for testing the association between the microbiome and a covariate of interest. Statistical significance is established by permutation, which is computationally intensive for large sample sizes. As large-scale microbiome studies, such as American Gut Project (AGP), become increasingly popular, a computationally efficient version of PERMANOVA is much needed. To achieve this end, we derive the asymptotic distribution of the PERMANOVA pseudo-F statistic and provide analytical P-value calculation based on chi-square approximation. We show that the asymptotic P-value is close to the PERMANOVA P-value even under a moderate sample size. Moreover, it is more accurate and an order-of-magnitude faster than the permutation-free method MDMR. We demonstrated the use of our procedure D-MANOVA on the AGP dataset.
Availability and implementation
D-MANOVA is implemented by the dmanova function in the CRAN package GUniFrac.
Supplementary information
Supplementary data are available at Bioinformatics online. |
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ISSN: | 1367-4803 1460-2059 1367-4811 |
DOI: | 10.1093/bioinformatics/btab498 |