shinyDeepGxP: a user-friendly R shiny app for predicting surface protein abundance from scRNA-seq expression using deep learning in blood cells
Hui-Mei Tsai, Tzu-Hung Hsiao, Yu-Ching Hsu, Li-Ju Wang, Yu-Chiao Chiu, Eric Y Chuang, Yidong Chen · 2026
Read shinyDeepGxP: a user-friendly R shiny app for predicting surface protein abundance from scRNA-seq expression using deep learning in blood cells by Hui-Mei Tsai, Tzu-Hung Hsiao, Yu-Ching Hsu, Li-Ju Wang, Yu-Chiao Chiu, Eric Y Chuang, Yidong Chen (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/PMC13532762.txt.
Description
Hui-Mei Tsai and colleagues present in 2026 shinyDeepGxP, a web app that predicts surface protein levels from single-cell RNA data. Protein levels shape what immune cells do, yet many datasets record RNA only because paired protein tests cost a lot and are hard to run. The app runs a deep learning model trained on blood cells.
Users upload RNA count tables and get predictions for 224 surface proteins, plus charts that help split cell groups. An explore mode shows which RNA signals drive each protein call and which pathways they touch. Readers without coding skills gain protein-level detail from RNA-only files.
Catalog record
| CREATOR | Hui-Mei Tsai, Tzu-Hung Hsiao, Yu-Ching Hsu, Li-Ju Wang, Yu-Chiao Chiu, Eric Y Chuang, Yidong Chen |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 23 KB |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |