![[feed]](/style/images/feed-icon-14x14.png){kind=icon}
Tools
Tools
Preview |
PDF (Original Article)
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
4MB |
![[thumbnail of Supplementary Information]](https://edoc.mdc-berlin.de/style/images/fileicons/other.png) |
Other (Supplementary Information)
4MB |
| Item Type: | Article |
|---|---|
| Title: | Shortcomings of silhouette in single-cell integration benchmarking |
| Creators: |
Rautenstrauch, Pia  ORCID: https://orcid.org/0000-0002-0070-4759 and Ohler, Uwe ORCID: https://orcid.org/0000-0002-0881-3116
|
| Abstract: | Single-cell studies rely on advanced integration methods for complex datasets affected by batch effects from technical factors alongside meaningful biological variation. Silhouette is an established metric for assessing unsupervised clustering results, comparing within-cluster cohesion to between-cluster separation. However, silhouette’s assumptions are typically violated in single-cell data integration scenarios. We demonstrate that silhouette-based metrics cannot reliably assess batch effect removal or biological signal conservation and propose more robust evaluation strategies. |
| Keywords: | Algorithms, Benchmarking, Cluster Analysis, Clustering Algorithms, Single-Cell Analysis, Animals |
| Source: | Nature Biotechnology |
| ISSN: | 1087-0156 |
| Publisher: | Nature Publishing Group |
| Volume: | 44 |
| Number: | 6 |
| Page Range: | 954-958 |
| Date: | June 2026 |
| Official Publication: | https://doi.org/10.1038/s41587-025-02743-4 |
| PubMed: | View item in PubMed |
| Related to: |
Repository Staff Only: item control page
