Submitted to: Soil Science Society of America Annual Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 10/1/2014
Publication Date: 11/3/2014
Publication URL: https://scisoc.confex.com/scisoc/2014am/webprogram/Paper89394.html
Citation: Manter, D.K., Bakker, M.G. 2014. Introducing OTUshuff and DwOdum: A new set of tools for estimating beta diversity for under-sampled communities. Soil Science Society of America Annual Meeting. https://scisoc.confex.com/scisoc/2014am/webprogram/Paper89394.html.
Technical Abstract: Characterization of complex microbial communities by DNA sequencing has become a standard technique in microbial ecology. Yet, particular features of this approach render traditional methods of community comparison problematic. In particular, a very low proportion of community members are typically sampled, and spurious taxa can be generated in datasets through a number of mechanisms (e.g., sequencing errors, incomplete sampling). A robust measure of distance between two microbial communities, as assessed by sequencing surveys, should correct for random differences due to incomplete sampling. We present a new analytical method, OTUshuff, which only considers OTU/taxon differences between communities that are statistically significant. We also propose a new distance measure, the weighted Odum (DwOdum) distance score. DwOdum is particularly suited to sequence-based characterization of microbial communities, as it has reduced sensitivity to differences in the abundance of rare taxa. We illustrate the utility of OTUshuff, DwOdum, and their combination, using simulated data as well as an actual soil microbial community pyrosequencing dataset derived from diverse sites and with plot-level replicates. The DOTUshuff-wOdum approach to estimating distance between communities successfully corrects over-estimation of distances when sampling is incomplete. DOTUshuff-wOdum also removes artificial variation among replicate sub-samples drawn from a common pool of sequence reads, while maintaining the ability to detect differences among plots and among sites.