Working with dietary DNA metabarcoding data? Unsure how to concisely summarize your workflow for publication? Tired of all the effort required to format your data tables for archiving in Dryad, supplementary materials, or other archives? The lab has posted new code to our GitHub repository that will help you solve all of these problems.

Over the years, our lab has contributed a number of essential reviews about how DNA sequence data can be accurately converted into dietary information. The science is clear: inappropriate assumptions about how to 'clean up' sequence data using bioinformatics can do more harm than good by warping our diet profiles and generating misleading assumptions. Nevertheless, we have to make some such assumptions to generate datasets that are useful and informative. How should we think about striking a balance between these competing imperatives?

Led by Dr. Bethan Littleford-Colquhoun, one of the more important reviews we've produced on this topic was published in Molecular Ecology: The Precautionary Principle. This review, and a follow-up reply describing Evidence-based Strategies to Navigate Complexity, tackle the challenge of identifying appropriate abundance-filtering strategies in DNA metabarcoding pipelines. This post provides an essential summary of what we found... 

For more than 13 years, we have built and maintained a plant DNA Barcode library for the flora of Mpala Research Centre in Kenya. Many versions have been released, the most substantial of which was associated withe 2019 publication of the Plant DNA-barcode library and community phylogeny for a semi-arid East African savanna in Molecular Ecology. This post is intended to help you track significant developments in this long-term collaborative effort and find the most current version to use in your analyses.