ADAMIXTURE is a fast CPU/GPU implementation of ADMIXTURE for biobank-scale genetic clustering. .P and .Q outputs remain compatible with ADMIXTURE.
Use Cases
Connectivity and dispersal mode shape the landscape genetics of a carnivorous pitcher plant-arthropod metacommunity
Authors: Nonno Hasegawa, Asa E. Conover, Matin Miryeganeh, David W. Armitage (2026)
Preprint: bioRxiv (DOI: 10.64898/2026.08.09.743144)
This study investigates how landscape connectivity, dispersal mode, and environmental resistance shape genetic structure in the carnivorous pitcher plant Darlingtonia californica (cobra lily) and two of its obligate arthropod mutualists (the midge Metriocnemus edwardsi and the mite Sarraceniopus darlingtoniae) sampled across sites in Oregon and northern California.
Application:
The authors used ADAMIXTURE to estimate individual ancestry proportions across a nuclear genomic dataset of 19,166 SNPs in 199 individuals. They evaluated ancestral components across K = 2 to 15 with 5-fold cross-validation, which supported K = 3–4 as the most plausible regional clustering structure. The results revealed limited admixture across regional boundaries, supporting the central–marginal hypothesis and demonstrating that gene flow in the host plant is restricted by landscape resistance rather than geographic distance alone.
JanusX: an integrated and high-performance platform for scalable genome-wide association studies and genomic selection
Authors: Jingxian Fu, Anqiang Jia, Haiyang Wang, Hai-Jun Liu (2026)
Preprint: bioRxiv (DOI: 10.64898/2026.01.20.700366)
JanusX is an integrated, high-performance computational platform developed for large-scale Genome-Wide Association Studies (GWAS) and Genomic Selection (GS), delivering up to 19× speedup over traditional tools like GEMMA for Linear Mixed Models (LMM).
Application:
JanusX directly integrates ADAMIXTURE through its fastpop module to perform rapid unsupervised population structure inference. This integration enables researchers to calculate ancestry matrices (Q matrices), generate stacked ancestry proportion bar plots, and control for population stratification directly inside automated high-throughput GWAS and genomic prediction pipelines without separate manual pre-processing.
Citation
If you use ADAMIXTURE in your research, please cite:
@article{saurina2026adamixture,
title={ADAMIXTURE: adaptive first-order optimization for biobank-scale genetic clustering},
author={Saurina-i-Ricos, Joan and Mas Montserrat, Daniel and Ioannidis, Alexander G.},
journal={Bioinformatics},
volume={42},
number={Supplement\_1},
pages={btag236},
year={2026},
doi={10.1093/bioinformatics/btag236},
url={https://doi.org/10.1093/bioinformatics/btag236}
}
Figure: Estimated individual ancestry proportions for Darlingtonia californica from ADAMIXTURE (K = 3, K = 4 supported by 5-fold CV).