FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies
Travis Canida, Zhenyao Ye, Shao-Hsuan Wang, Hsin-Hsiung Huang, Yezhi Pan, Menglu Liang, Shuo Chen, Tianzhou Ma, Lin S Chen, Lin S Chen, Xiaofeng Zhu, Lin S Chen, Xiaofeng Zhu, Lin S Chen, Xiaofeng Zhu, Lin S Chen, Xiaofeng Zhu · 2026
Read FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies by Travis Canida, Zhenyao Ye, Shao-Hsuan Wang, Hsin-Hsiung Huang, Yezhi Pan, Menglu Liang, Shuo Chen, Tianzhou Ma, Lin S Chen, Lin S Chen, Xiaofeng Zhu, Lin S Chen, Xiaofeng Zhu, Lin S Chen, Xiaofeng Zhu, Lin S Chen, Xiaofeng Zhu (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13581217.txt.
Description
Travis Canida leads a team introducing FM-GPT, a statistical method for finding causal genes across many traits at once, in a paper published in two thousand twenty-six. Transcriptome-wide association studies link genes to traits by combining genetic and expression data. Correlated genes and linkage can fabricate false signals.
Fine mapping sorts real culprits from neighbors. Phenome-wide studies complicate that task with hundreds of related phenotypes of mixed types. FM-GPT is a Bayesian method built for exactly that setting. It prioritizes putatively causal genes across correlated traits jointly. Continuous, binary, count, and multinomial outcomes are all handled. The authors position the tool for the era of electronic health record genetics.
Catalog record
| CREATOR | Travis Canida, Zhenyao Ye, Shao-Hsuan Wang, Hsin-Hsiung Huang, Yezhi Pan, Menglu Liang, Shuo Chen, Tianzhou Ma, Lin S Chen, Lin S Chen, Xiaofeng Zhu, Lin S Chen, Xiaofeng Zhu, Lin S Chen, Xiaofeng Zhu, Lin S Chen, Xiaofeng Zhu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 100 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |