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Resources

This page is dedicated to sharing front-facing resources for a variety of areas of my work for which I would like to reduce barriers to entry (including but not limited to R coding, bioinformatics, and taxonomy). Some tutorials are cross-posted on GitHub. 

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Code to quantify and characterize the number of unique diet groupings that exist within a population or community. The strategy is based on a simple machine-learning algorithm and described in the Hoff et al (2025) PNAS paper. Links to the open-source code and data repositories are below.

Zenodo: https://doi.org/10.5281/zenodo.15634157

Dryad: https://doi.org/10.5061/dryad.mgqnk99b8

Code from Hoff et al. 2025 PNAS paper

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This tutorial walks through the steps of making informative and visually striking maps in R. From the most basic building blocks, we add detail using well-developed R packages. The resulting map displays the locations of your study sites or sample collections. In an effort to make these tutorials more interactive, my GitHub page includes both a code pipeline and some example data that can be fed directly into the code.

Map-making in R for ecologists

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Coming soon on Brown Digital Repository

Global DNA reference library - trnL-P6

  • GitHub

Hannah Hoff

Copyright 2025 © Hannah Hoff

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