New feature on our Software & Data repository page: Hot off the press! Featuring code from Hannah Hoff's 2025 PNAS paper, The Apportionment of Dietary Diversity in Wildlife.

This paper presented a potentially paradigm-shifting strategy to quantify and characterize the number of unique 'diet types' 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, which used the community of migratory large mammalian herbivores -- such as bison and elk -- as a prime example.

Fans of the lab will be very excited to see this much-anticipated release of our standard dietary DNA metabarcoding pipeline, with a walk-through easily accessible on the centralized "Software & Data" section of our webpage. Until now, people would have to access code repositories associated with each of our publications or contact us directly to model their analysis after our well-established workflow. That led to multiple versions of the pipeline in circulation, since we are constantly improving it and published versions quickly ended up out of date. We have tried to solve that problem by...

Beginning in June, we have increasingly made our internal lab methods publicly visible on the "Protocols" section of our webpage. We began with some of the most frequently requested protocols that speak to the unique strengths of our lab's work and experience, featuring field-to-lab protocols for collecting and banking dietary samples, parasite samples, and plant barcode samples. We have expanded to include...

Featured Software from the Kartzinel Lab: Geographic Coverage of DNA Barcodes. The inaugural code repository to be highlighted in our Featured Software section of the Software & Data page presents the Quarto Code Book published in association with our Molecular Ecology Review Paper, "Global Availability of Plant DNA Barcodes as Genomic Resources to Support Basic and Policy-Relevant Biodiversity Research" can be easily modified to evaluate the geographic coverage of other data sets. Although the featured code emphasizes geographic coverage from our work in Yellowstone National Park...

Over the past couple of years, a lot of things have changed. Some of those changes have brought improvements to the way we share the software and data that we generate in the lab, necessitated in part by the growing popularity of our work to a point that we recognized a substantial benefit to enhancing our commitment to easy access and open-source principles. 

To make it easier to find and access our most in-demand repositories -- often spread across a variety of platforms including GitHub, Zenodo, NCBI, BOLD, etc. -- we have created a main landing page on the website where we have curated a mix of both recent and timeless contributions to the field. Check it out!

You might also want to check out our lab's main GitHub repository, where we are increasingly making our projects publicly available so you can benefit from any updates we've made since posting a version of record for the code with a prior publication (e.g., a static record with a Zenodo DOI). 

I will periodically post updates to this blog in order to highlight and summarize important updates to help ensure the community is aware, but we will no longer be using these pages to share data or code directly as we have in the past.