NANUQ+: A divide-and-conquer approach to network estimation
Abstract Inference of a species network from genomic data remains a difficult problem, with recent progress mostly limited to the level-1 case. However, inference of the Tree of Blobs of a network, showing only the network’s cut edges, can be performed for any network by TINNiK, suggesting a divide-...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
|
| Series: | Algorithms for Molecular Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13015-025-00274-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Abstract Inference of a species network from genomic data remains a difficult problem, with recent progress mostly limited to the level-1 case. However, inference of the Tree of Blobs of a network, showing only the network’s cut edges, can be performed for any network by TINNiK, suggesting a divide-and-conquer approach to network inference where the tree’s multifurcations are individually resolved to give more detailed structure. Here we develop a method, $$\text {NANUQ}^+$$ NANUQ + , to quickly perform such a level-1 resolution. Viewed as part of the NANUQ pipeline for fast level-1 inference, this gives tools for both understanding when the level-1 assumption is likely to be met and for exploring all highly-supported resolutions to cycles. |
|---|---|
| ISSN: | 1748-7188 |