From gene correlations to cell clusters: COTAN improved scRNA-seq analysis
Silvia Giulia Galfrè, Marco Fantozzi, Alina Sîrbu, Irene Testa, Matteo Tolloso, Andrea Alberti, Corrado Priami, Francesco Morandin · 2026
Read From gene correlations to cell clusters: COTAN improved scRNA-seq analysis by Silvia Giulia Galfrè, Marco Fantozzi, Alina Sîrbu, Irene Testa, Matteo Tolloso, Andrea Alberti, Corrado Priami, Francesco Morandin (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-13191298.txt.
Description
Single-cell RNA sequencing reads the active genes in thousands of cells at once, but the data are sparse: most entries are zero. Silvia Galfrè and co-authors present an improved version of their COTAN workflow, which works from gene correlations and models the zeros directly. It skips the reshaping steps that standard pipelines borrow from bulk data work.
Those standard steps can distort true zeros and throw away quiet but important genes. COTAN instead needs no scaling or gap filling and is tuned for droplet data. Tests on public data sets show it finds marker genes better than leading tools, including very quiet ones. Its scores can also spot mixed cell groups and confirm when a cluster is truly uniform. The authors offer it as a full, biology-first path from raw counts to cell clusters.
Catalog record
| CREATOR | Silvia Giulia Galfrè, Marco Fantozzi, Alina Sîrbu, Irene Testa, Matteo Tolloso, Andrea Alberti, Corrado Priami, Francesco Morandin |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 44 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |