Bioinformatics (Oxford, England) · 2026
GROMTools: scalable individual-level GReX imputation for mega-biobank-scale cohorts.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Anyfantakis Marios, Venkatesh Sanan, Bennett Jamie J R, Liu Chenyu, Hoffman Gabriel E, Roussos Panos, Voloudakis Georgios
Аннотация
MOTIVATION: The computational burden of individual-level genetically regulated gene expression (GReX) imputation has risen sharply with the growth of human mega-biobanks and the rapid expansion of transcriptomic imputation models across tissues and single-cell hierarchies. Existing tools were not designed for this setting and require complex, memory-intensive workflows that are poorly matched to shared and cloud-based compute environments, where runtime, memory, and I/O directly determine cost and throughput. GROMTools is an open-source C ++ engine with an R interface that exploits sparse prediction weights, streams PLINK2 genotypes, and writes compact binary outputs for scalable individual-level GReX imputation.
RESULTS: In UK Biobank (UKB), benchmarks on chromosome 1 across 50,000-450,000 individuals, 388,017 variants, and 11,724 gene-model pairs from 32 single-nucleus transcriptome imputation models, GROMTools produced near-identical predictions to PrediXcan and PLINK2, with minimum Pearson correlation >0.999 and maximum RMSE <0.001 across all of the imputed genes, while reducing CPU time by about 100-fold and peak memory by about 33-fold. These gains make routine biobank-scale individual-level GReX imputation practical and cost-efficient on standard CPU infrastructure.
AVAILABILITY: GROMTools is freely available at https://github.com/voloudakislab/gromtools under the GPL v3 license. Documentation is available at https://voloudakislab.github.io/gromtools/ .All scripts used for data quality control and benchmarking, together with log files and a snapshot of the GROMTools code version used for all of our analyses, are archived at DOI:https://zenodo.org/records/21926165.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
RESULTS: In UK Biobank (UKB), benchmarks on chromosome 1 across 50,000-450,000 individuals, 388,017 variants, and 11,724 gene-model pairs from 32 single-nucleus transcriptome imputation models, GROMTools produced near-identical predictions to PrediXcan and PLINK2, with minimum Pearson correlation >0.999 and maximum RMSE <0.001 across all of the imputed genes, while reducing CPU time by about 100-fold and peak memory by about 33-fold. These gains make routine biobank-scale individual-level GReX imputation practical and cost-efficient on standard CPU infrastructure.
AVAILABILITY: GROMTools is freely available at https://github.com/voloudakislab/gromtools under the GPL v3 license. Documentation is available at https://voloudakislab.github.io/gromtools/ .All scripts used for data quality control and benchmarking, together with log files and a snapshot of the GROMTools code version used for all of our analyses, are archived at DOI:https://zenodo.org/records/21926165.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.