Lense: optimizing data preprocessing in single-cell omics using large language models
Jingyun Liu, Zhicheng Ji · 2026
Read Lense: optimizing data preprocessing in single-cell omics using large language models by Jingyun Liu, Zhicheng Ji (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-13235726.txt.
Description
Jingyun Liu and Zhicheng Ji introduce this 2026 tool that uses a language model to tune the first steps of single-cell data analysis. Before single-cell data can be read, it must be cleaned and reduced, and default settings often underperform on new data types like spatial maps. Lense compares pictures of the data under different prep recipes and picks the best. Built into a popular analysis package, it needs no hand tuning and aims to make early analysis sturdier across varied data sets.
Catalog record
| CREATOR | Jingyun Liu, Zhicheng Ji |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 31 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |