Jiayi Li

The study introduces OpenLipid, a large language model (LLM)-based workflow for targeted DIA lipidomics that builds assay libraries from DDA results and, in a zero-shot setting, directly evaluates extracted ion chromatograms (XICs) from DIA data to select target lipid peaks and produce human-readable rationales; across four human plasma and mouse feces datasets in positive and negative ionization modes it identified 55.3%/19.0% (plasma) and 71.8%/31.8% (feces) of library targets at 5% FDR, comparable overall to DIAMetAlyzer (57.8%/19.7%, 89.0%/17.8%) and substantially higher than untargeted MS-DIAL DIA (12.6%/0.0%, 47.5%/0.

The study introduces OpenLipid, a large language model (LLM)-based workflow for targeted DIA lipidomics that builds assay libraries from DDA results and, in a zero-shot setting, directly evaluates extracted ion chromatograms (XICs) from DIA data to select target lipid peaks and produce human-readable rationales; across four human plasma and mouse feces datasets in positive and negative ionization modes it identified 55.3%/19.0% (plasma) and 71.8%/31.8% (feces) of library targets at 5% FDR, comparable overall to DIAMetAlyzer (57.8%/19.7%, 89.0%/17.8%) and substantially higher than untargeted MS-DIAL DIA (12.6%/0.0%, 47.5%/0.