Article
NAToRA, a relatedness-pruning method to minimize the loss of dataset size in genetic and omics analyses
Registro en:
LEAL,Thiago Peixoto et al. NAToRA, a relatedness-pruning method to minimize the loss of dataset size in genetic and omics analyses. Comput Struct Biotechnol J., v. 20, p. 1821–1828, 2022. doi: 10.1016/j.csbj.2022.04.009
2001-0370
Autor
Leal, Thiago Peixoto
Furlan, Vinicius C
Gouveia, Mateus Henrique
Duarte, Julia Maria Saraiva
Fonseca, Pablo AS
Tou, Rafael
Scliar, Marilia de Oliveira
Araujo, Gilderlanio Santana de
Costa, Lucas F.
Zolini, Camila
Peixoto, Maria Gabriela Campolina Diniz
Carvalho, Maria Raquel Santos
Costa, Maria Fernanda Furtado Lima
Gilman, Robert H
Tarazona-Santos, Eduardo
Rodrigues, Maíra Ribeiro
Resumen
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.