Scalable high resolution ancestry deconvolution for genomic data
Helgi Hilmarsson, Arvind S Kumar, Míriam Barrabés, Richa Rastogi, Carlos D Bustamante, Daniel Mas Montserrat, Alexander G Ioannidis · 2026
Read Scalable high resolution ancestry deconvolution for genomic data by Helgi Hilmarsson, Arvind S Kumar, Míriam Barrabés, Richa Rastogi, Carlos D Bustamante, Daniel Mas Montserrat, Alexander G Ioannidis (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/PMC13518915.txt.
Description
Helgi Hilmarsson leads a seven-author team presenting Gnomix in 2026, software that labels the ancestry of each DNA segment in people and animals with mixed heritage. Local ancestry inference powers studies of population history and ancestry-linked traits, yet older methods scale badly to biobank-sized data, deep time, and many source populations.
Gnomix bundles several inference methods that beat existing tools on both accuracy and speed, with shareable trained models that expose no private training genomes. A companion tool, Gnofix, corrects phasing errors quickly. Tests on worldwide human and dog genomes dated ancient New World segments in the Xoloitzcuintli dog breed back over 100 generations, showing the fine resolution achieved.
Catalog record
| CREATOR | Helgi Hilmarsson, Arvind S Kumar, Míriam Barrabés, Richa Rastogi, Carlos D Bustamante, Daniel Mas Montserrat, Alexander G Ioannidis |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 67323 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |