{
  "id": 12908188,
  "title": "Robust ORF Deconvolution from Multiple Ribo-seq Datasets with Group LASSO Penalty",
  "url": "https://urgent.news/2026/10/08/robust-orf-deconvolution-from-multiple-ribo-seq-datasets-with-group",
  "topic": "science",
  "section": "Science",
  "published": "2026-10-08T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.10.01.755973v1?rss=1"
  },
  "original_language": "en",
  "account": "Ribo-seq technology has revealed the existence of numerous translated but uncharacterized ORFs (Open Reading Frames). Although there is mounting evidence supporting the presence of cryptic ORFs from peptidomics data, identifying weakly translated, short, and overlapping ORFs has remained a significant challenge. To address this issue, researchers have developed PRICE 2, a novel method that integrates concepts from isoform deconvolution to resolve these complex translation events.\n\nPRICE 2 utilizes a generative model in conjunction with group LASSO regularized regression. This combination allows the tool to jointly estimate active ORFs across multiple sequencing runs. In a thorough evaluation, PRICE 2 demonstrated superior performance compared to thirteen leading tools in detecting both short and overlapping ORFs. Additionally, orthogonal validation using immunopeptidomics showed that ORFs identified by PRICE 2 can facilitate the discovery of approximately 40% more cryptic MHC-I peptides compared to the best-performing competing tool at a fixed false discovery rate.\n\nTo further validate the effectiveness of PRICE 2, researchers analyzed public ribo-seq data from 45 diverse cell and tissue types. This analysis led to the construction of ORF-stock, a comprehensive database containing non-canonical ORFs specifically tailored for immunopeptidomic studies.",
  "summary": "Ribo-seq has provided compelling evidence that there are many translated but unannotated ORFs. Despite a growing body of peptidomic support for cryptic ORFs, the computational discovery of weakly translated, short and mutually overlapping ORFs has remained a major bottleneck. Here we introduce PRICE 2, a method designed to resolve these challenging translation events by adapting concepts from…",
  "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."
}