Team Glass Box

I built HAR-annotator, a glass-box pipeline for ranking Human Accelerated Regions — short stretches of DNA that stayed frozen across mammals for a hundred million years, then changed fast only on the human lineage, making them prime suspects for what reshaped the human brain. There are thousands of them, and which ones matter depends entirely on the question you bring. That's the whole design: the pipeline doesn't hand you one fixed answer, it lets you ask a question and shows its full reasoning. The question I brought was just one instance (which HARs are relevant to neurodevelopment and disease?) and the tool is built so anyone can bring a different one. The pipeline works as a funnel followed by a score. Starting from all 3,257 HARs (from this Nature paper https://www.nature.com/articles/s41586-025-08622-x), three biologically motivated gates narrow the field based on information from 5 datasets: keep what’s genuinely conserved across mammals (mean 241-way phyloP above 1.0), then what sits near a known neurodevelopmental-disease gene (proximity within 1 Mb), and then what overlaps a neuropsychiatric GWAS signal. This funnel 3257 HARs into 363 candidate HARs of interest. Each of the 363 survivors is then scored on seven normalized axes combined into one weighted sum: in my investigation into neurodevelopment and disease relevance, gene link and disease genetics carry the most weight (0.22 each), then constraint (0.18), fetal-brain chromatin activity and developmental timing (0.13 each), and human–chimp acceleration and TF-motif disruption weighted low (0.07 and 0.05) because they're first-order or model-based signals. Every axis's contribution ships as its own column, so each rank decomposes into its reasons: the top hit near ZSWIM6 is carried by conservation and gene link, while a lower hit near RPS23 has a strong gene link but barely any conservation. Nothing is hidden in a model. What I found for my question: at the top is a HAR sitting near ZSWIM6, a brain-development gene. It ranks first because it's deeply conserved, carries the strongest human–chimp acceleration signal in the whole top tier, and sits in open, active chromatin in the developing brain. Just behind it, essentially tied, are HARs near TCF20 and POC1B, and each earns its rank differently: TCF20 is a well-established neurodevelopmental-disorder gene, while POC1B rides mostly on its disease-signal axis. Because the score decomposes, you can see exactly why each one placed. The broader shortlist recovers a who's-who of neurodevelopment genes (ZEB2, TCF4, MEF2C, FOXP2, SOX5) without any of them being hard-coded in, which is a good sign the scoring is tracking real biology. And it's robust: across 20,000 random weightings the ranking barely moves (see the weight_eval folder in my GitHub). Most strikingly, it isn't just resurfacing famous genes, ZSWIM6 ranks first despite having only 27 abstracts on PubMed, so the pipeline is pointing at genuinely under-studied biology rather than re-confirming what's already well known. But the more important result is that the tool answers other questions too. Relax the funnel and the candidate set opens up (577 elements if you drop the rare-disease requirement, 2,757 on conservation alone) and re-scoring reshuffles the podium (TCF20 overtakes ZSWIM6, new genes appear). Change the weights and it re-sorts around what you value. Same evidence, different question, different defensible shortlist. Overall, the same HARs that may have made us human also keep showing up next to genes for autism and schizophrenia which means that the thing that built us may be the same thing that makes us vulnerable. This is a reproducible tool that turns thousands of undifferentiated candidates into an auditable shortlist (and reshapes that shortlist around whatever question a researcher actually has). This can hopefully serve as a hypothesis generator many labs can point at their own biology, not just a one-off analysis of mine.