Statistical analysis for marker gene studies

Description

This tool produces several visualizations (rarefaction and rank-abundance curves and an RDA plot), and compares the diversity between groups of samples using several ANOVA-type of analyses. It also performs indicator species analysis and contribution diversity approach.

Parameters

Details

This tool takes two input files: a count table that contains the counts of the identified species or operational taxonomic units (OTUs) in each sample, and a phenodata table that describes the grouping of the samples. Statistical tests only work for datasets which contain 2-3 groups. The analyses are based on the functionality of the R packages vegan, rich, biodiversityR, pegas and labdsv.

Visual data analysis

Statistical data analysis

Output

The analysis output consists of the following:

References

Consult the R packages vegan, rich, biodiversityR, pegas and labdsv for more details about the methods.

Excoffier, L., Smouse, P. E. and Quattro, J. M. (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics, 131, 479-491.
Anderson, M.J. 2001. A new method for non-parametric multivariate analysis of variance. Austral Ecology, 26: 32-46.
Anderson, M.J. (2006) Distance-based tests for homogeneity of multivariate dispersions. Biometrics 62, 245-253.
Lu, H. P., Wagner, H. H. and Chen, X. Y. 2007. A contribution diversity approach to evaluate species diversity. Basic and Applied Ecology, 8, 1-12.
Dufrene, M. and Legendre, P. 1997. Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol. Monogr. 67(3):345-366.
Aho, K., D.W. Roberts, and T.W.Weaver. 2008. Using geometric and non-geometric internal evaluators to compare eight vegetation classification methods. J. Veg. Sci. In press.