2025 · Bioinformatics · Oxford University Press · added 2026-04-21
Motivation: Rare diseases affect over 300 million people worldwide and are often caused by genetic variants. While variant detection has be come cost-effective, interpreting these variants—particular Show more
Motivation: Rare diseases affect over 300 million people worldwide and are often caused by genetic variants. While variant detection has be come cost-effective, interpreting these variants—particularly collecting literature-based evidence like ACMG/AMP PM3—remains complex and time-consuming. Results: We present AutoPM3, a method that automates PM3 evidence extraction from literatures using open-source large language models (LLMs). AutoPM3 combines a Text2SQL-based variant extractor and a retrieval-augmented generation (RAG) module, enhanced by a variantspecific retriever and fine-tuned LLM, to separately process tables and text. We curated PM3-Bench, a dataset of 1027 variant-publication Show less