{
  "id": 18500900,
  "title": "QRAFT: Scaling coalescent-based species tree inference to one million taxa",
  "url": "https://urgent.news/2026/11/06/qraft-scaling-coalescent-based-species-tree-inference-to-one-million",
  "topic": "ai",
  "section": "AI",
  "published": "2026-11-06T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.11.05.764586v1?rss=1"
  },
  "original_language": "en",
  "account": "Astrophysicists have unveiled QRAFT, a groundbreaking method for estimating species trees from phylogenomic datasets, now spanning hundreds of thousands of species. This innovative algorithm boasts near-linear running time of O(kn log^2 n) when its recursion is balanced, nearly matching the O(kn) time required solely to read the input. QRAFT further stands out with its asymptotically optimal O(kn) memory usage, scaling linearly with input size. The method successfully infers a million-taxon species tree from 1,000 genes in just three hours using modest resources - 298 GB of RAM, 64 CPU threads, and no GPUs. In comparison, the ASTRAL-MP method, a parallel implementation of the widely used ASTRAL algorithm, would take approximately 36 years to accomplish the same task, demanding impractically large memory resources. Despite this, QRAFT maintains accuracy comparable to, and in some cases superior to, leading species tree estimation techniques. A notable achievement involves reconstructing a microbial tree of life comprising an astounding 199,330 genomes in mere hours, employing modest CPU resources. This significant advancement places highly accurate, statistically consistent coalescent-based species tree inference within reach of the million-taxon regime, paving the way for comprehensive phylogenomic analyses encompassing the entire tree of life. QRAFT is now publicly accessible at https://github.com/risenfromashes/qraft.",
  "summary": "Species tree inference from multi-locus data under the multispecies coalescent has not kept pace with phylogenomic datasets that now span hundreds of thousands of species. We present QRAFT, a statistically consistent method for estimating species trees by maximizing quartet support on phylogenomic datasets at unprecedented scales. For n taxa and k gene trees, QRAFT achieves near-linear running…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}