153 - Seebot

In Part 2 of Ancient problems require ancient solutions, host Nabil Ali Khan brings James Fellows Yates back to the mic to go deeper into how ancient metagenomics actually gets done. They dig into dental calculus — mineralised plaque whose bone-like hydroxyapatite locks DNA in place for tens of thousands of years (James recovered a microbiome from a 100,000-year-old Neanderthal), what it tells us about diet, dysbiosis and the rise of dental disease after the Neolithic, and even a coming paper on a famous historical Briton with the highest ancient-DNA yield ever seen from calculus. Then it's onto the tooling: the origin story of nf-core/eager, why ancient DNA still needs a 10-year-deprecated GATK unified genotyper, the birth of the now-ubiquitous nf-core Metro-Map pipeline diagrams, and how James and the SPAAM community wrote the open textbook Introduction to Ancient Metagenomics as a practical guide for anyone — bioinformatician or historian — walking into the field. Guest: James Fellows Yates Hosts: Dr Nabil Ali Khan, Dr Lee Katz, Prof Andrew Page Introduction to Ancient Metagenomics (open textbook) — https://www.spaam-community.org/intro-to-ancient-metagenomics-book/ SPAAM community — https://spaam-community.org nf-core/eager — https://nf-co.re/eager AncientMetagenomeDir — https://github.com/SPAAM-community/AncientMetagenomeDir AMDirT — https://github.com/SPAAM-community/AMDirT nf-core Metro-Map guide — https://nf-co.re/docs/contributing/tutorials/creating_with_nf_core_tools#metro-map

What can DNA recovered from bones, teeth and paleofaeces tell us that living samples can't — and how do you keep modern contamination from drowning out a 1,000-year-old signal? In Part 1, host Nabil Ali Khan is joined by James Fellows Yates (bioinformatician, biomolecular archaeologist, and editor of the new open textbook Introduction to Ancient Metagenomics) for a tour of the field. They cover why ancient DNA arrives as 30–70 bp fragments with characteristic C→T "smiley plot" damage, how endogenous yields as low as 1% still count as a good sample, and the wet-lab lengths (bodysuits, UV, no kits) needed to keep libraries clean. They also dig into the big questions ancient microbial DNA is now answering — plague and TB origins, oral-microbiome loss since the Neolithic, AMR trends read from historical bear calculus — and how the SPAAM community, NF-core/eager and AncientMetagenomeDir grew up to support the work. Guest: James Fellows Yates Hosts: Dr Nabil Ali Khan, Dr Lee Katz, Prof Andrew Page SPAAM community — https://spaam-community.org nf-core/eager — https://nf-co.re/eager AncientMetagenomeDir — https://github.com/SPAAM-community/AncientMetagenomeDir Introduction to Ancient Metagenomics (open textbook) — https://www.spaam-community.org/intro-to-ancient-metagenomics-book/

Nabil, Andrew, and Lee talk with Liyang Diao and Valisha Shah from the nonprofit organization, Boston Women in Bioinformatics, a community that supports bioinformaticians in the Greater Boston area. We discuss the organization’s mission, the resources it provides, and what’s coming next for the group. boston-wib.org/

- Seebot https://github.com/happykhan/seebot - Ten quick tips to SNIFF out sustainable and secure scientific software | PLOS Computational Biology https://bsky.app/profile/stephenturner.us/post/3mqpkezwzls2m - Ten recommendations for creating usable bioinformatics command line software https://link.springer.com/article/10.1186/2047-217X-2-15

In this follow-up Software Deep Dive episode, we continue our conversation with Dr. Bede Constantinides (University of Birmingham) about the design and implementation of Deacon, a fast host-read removal tool for metagenomics. Deacon uses minimizers and k-mer set membership queries instead of alignment, allowing it to filter reads extremely quickly while balancing sensitivity and specificity. The tool is written in Rust, producing a small, fast binary and enabling very high throughput. We also discuss benchmarking with diverse viral and bacterial datasets, why tools like Kraken2 are not always ideal for host depletion, and why host read removal remains an unsolved problem—especially when balancing privacy, computational cost, and preservation of microbial reads. Links Deacon https://github.com/bede/deacon Hostile https://github.com/bede/hostile/ Bede Constantinides http://bede.im/ Kraken2 https://ccb.jhu.edu/software/kraken2/

In this Software Deep Dive episode, we talk with Dr. Bede Constantinides (University of Birmingham) about Deacon, a tool for removing host DNA reads from metagenomic datasets. We discuss why host read removal is a deceptively difficult problem, the limitations of alignment-based approaches, and how Deacon evolved from Bede's earlier tool Hostile. The conversation covers practical issues such as human contamination in metagenomes, balancing sensitivity vs specificity when filtering reads, and the computational challenges of working with large human reference datasets and pangenomes. This episode focuses on the background and motivation for Deacon. The next episode will dive deeper into how the method works. Links Deacon https://github.com/bede/deacon Hostile https://github.com/bede/hostile/ Bede Constantinides http://bede.im/ nf-core taxprofiler https://nf-co.re/taxprofiler Kraken2 https://ccb.jhu.edu/software/kraken2/

In this episode, Lee, Nabil, and Andrew experiment with “vibe coding” bioinformatics tools using AI coding assistants. The goal: quickly build useful genomics utilities that run entirely in the browser via WebAssembly, without requiring command-line installs or servers. Nabil states: “Even if you don’t want to use this technology, you should pay attention - because everyone else will.” They discuss how existing bioinformatics programs can be compiled to WebAssembly and wrapped with simple browser interfaces so analyses run locally on a user’s machine. This keeps genomic data private while making tools easier to access. The prototype tools discussed in the episode are available here: https://genomicx.github.io/ These examples show how browser-based bioinformatics might work for lightweight tasks such as genome comparisons and basic sequence analysis. Topics Covered * Using AI tools to rapidly prototype bioinformatics software * Compiling genomics programs to WebAssembly * Running analyses locally in the browser * Privacy advantages of keeping genomic data on the user’s computer * Practical limits of browser-based computation Try the tools and let us know what you think using the hashtag #genomicx

Join hosts Kieren Sharma (Artificially Ever After podcast, University of Bristol) and Andrew Page (MicroBinfie podcast, Origin Sciences) for a compelling live panel discussion exploring the dynamic intersection of artificial intelligence and the biosciences. In this episode, our expert panel discusses: 🔬 The AI Revolution in Biology - How machine learning and deep learning have transformed everything from microscopy image processing to drug discovery, enabling researchers to move from analyzing single images to conducting statistical analysis on massive datasets. 🤖 The LLM Era - Real experiences with generative AI tools like ChatGPT and Claude in research workflows, from accelerating literature reviews to writing thousands of lines of code through prompt engineering rather than manual coding. ⚖️ Finding Balance - When AI is genuinely transformative versus when it's just hype, including practical guidance on choosing between sophisticated transformer models and simpler, more energy-efficient approaches like random forests. 🔒 Safety & Trust Challenges - The "lethal trifecta" of untrusted data, private information, and internet access; reproducibility concerns; and the critical importance of validation in scientific AI applications. 🤝 Building Interdisciplinary Bridges - Honest insights about the mutual trust deficit between biologists and data scientists, the importance of finding a "buddy" in the other discipline, and why starting with the biological problem (not the model) is essential for meaningful results. 💡 Practical Advice for Computer Scientists - What skills and mindsets are needed to successfully apply computational expertise to new domains, from understanding domain-specific language to recognizing the complexity of biological problems. Featured Panelists: Dr. Mark Basham - Science Director for AI and Informatics, Rosalind Franklin Institute Dr. Elisa Pedone - Senior Research Scientist, CellVoyant (AI for cell therapy development) James Thomas - Senior Data Scientist, Jean Golding Institute, University of Bristol Key Themes: AI in drug discovery • machine learning in microscopy • generative AI in research • interdisciplinary collaboration • data quality challenges • environmental impact of AI • the future of computational biology This episode was recorded live at the Bridging AI & Biosciences Workshop in the University of Bristol and is part of AIBio UK's mission to highlight innovative applications of artificial intelligence across the biosciences.

Final part of our discussion/debate on NextFlow

Part two of debating NextFlow