ArticleComputational and structural biotechnology journal2022
NAToRA, a relatedness-pruning method to minimize the loss of dataset size in genetic and omics analyses.
Article in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Effect of ancestry and shared genetic architecture of serious mental illness on symptoms and cognition in an admixed Latin American population.Research square · 2026Article
- Effect of ancestry and shared genetic architecture of serious mental illness on symptoms and cognition in an admixed Latin American population.medRxiv : the preprint server for health sciences · 2026Article
- Unraveling the genetic landscape and admixture dynamics of urban populations across Peru.Communications biology · 2026Article
- Polygenic risk scores and Parkinson's disease in South Africa advancing ancestry informed disease prediction.PLoS genetics · 2026Article
- Insights into X-Linked Susceptibility to Parkinson's Disease in the South African Population.medRxiv : the preprint server for health sciences · 2025Article
- Polygenic risk scores and Parkinson's disease in South Africa: Moving towards ancestry-informed disease prediction.medRxiv : the preprint server for health sciences · 2025Article
- ESR1 Variants and Subcontinental Genomic Ancestry: Insights from the 1000 Genomes Project and Native American Populations.Clinical pharmacology and therapeutics · 2025Article
- Subcontinental genetic variation in the All of Us Research Program: Implications for biomedical research.American journal of human genetics · 2025Article
- Clinical and genetic insights of Parkinson's Disease in a Mexican cohort: highlighting Latino's diversity.medRxiv : the preprint server for health sciences · 2025Article
- Peruvian Population Genomics: Unraveling the Genetic Landscape and Admixture Dynamics of Urban Populations.bioRxiv : the preprint server for biology · 2025Article
- Chromosome X-wide common variant association study in autism spectrum disorder.American journal of human genetics · 2025Article
- Genetics of Latin American Diversity Project: Insights into population genetics and association studies in admixed groups in the Americas.Cell genomics · 2024Article
- Chromosome X-Wide Common Variant Association Study (XWAS) in Autism Spectrum Disorder.medRxiv : the preprint server for health sciences · 2024Article
- Population genomics of the invasive Northern Giant Hornet Vespa mandarinia in North America and across its native range.Scientific reports · 2024Article
- Comparing the effect of imputation reference panel composition in four distinct Latin American cohorts.bioRxiv : the preprint server for biology · 2024Article
- Human leukocyte antigen-DQA1*04:01 and rs2040406 variants are associated with elevated risk of childhood Burkitt lymphoma.Communications biology · 2024Article
- Sickle cell allele HBB-rs334(T) is associated with decreased risk of childhood Burkitt lymphoma in East Africa.American journal of hematology · 2024Article
- Unappreciated subcontinental admixture in Europeans and European Americans and implications for genetic epidemiology studies.Nature communications · 2023Article
- X-Chromosome Association Study in Latin American Cohorts Identifies New Loci in Parkinson's Disease.Movement disorders : official journal of the Movement Disorder Society · 2023Article
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16 authors.
Funding
Abstract
Genetic and omics analyses frequently require independent observations, which is not guaranteed in real datasets. When relatedness cannot be accounted for, solutions involve removing related individuals (or observations) and, consequently, a reduction of available data. We developed a network-based relatedness-pruning method that minimizes dataset reduction while removing unwanted relationships in a dataset. It uses node degree centrality metric to identify highly connected nodes (or individuals) and implements heuristics that approximate the minimal reduction of a dataset to allow its application to complex datasets. When compared with two other popular population genetics methodologies (PLINK and KING), NAToRA shows the best combination of removing all relatives while keeping the largest possible number of individuals in all datasets tested and also, with similar effects on the allele frequency spectrum and Principal Component Analysis than PLINK and KING. NAToRA is freely available, both as a standalone tool that can be easily incorporated as part of a pipeline, and as a graphical web tool that allows visualization of the relatedness networks. NAToRA also accepts a variety of relationship metrics as input, which facilitates its use. We also release a genealogies simulator software used for different tests performed in this study.
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