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GWLD: an R package for genome-wide linkage disequilibrium analysis

Linkage disequilibrium (LD) analysis is fundamental to the investigation of the genetic architecture of complex traits (e.g. human disease, animal and plant breeding) and population structure and evolution dynamics. However, until now, studies primarily focus on LD status between genetic variants lo...

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Detalles Bibliográficos
Autores principales: Zhang, Rong, Wu, Huaxuan, Li, Yasai, Huang, Zehang, Yin, Zongjun, Yang, Cai-Xia, Du, Zhi-Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10468308/
https://www.ncbi.nlm.nih.gov/pubmed/37431944
http://dx.doi.org/10.1093/g3journal/jkad154
Descripción
Sumario:Linkage disequilibrium (LD) analysis is fundamental to the investigation of the genetic architecture of complex traits (e.g. human disease, animal and plant breeding) and population structure and evolution dynamics. However, until now, studies primarily focus on LD status between genetic variants located on the same chromosome. Moreover, genome (re)sequencing produces unprecedented numbers of genetic variants, and fast LD computation becomes a challenge. Here, we have developed GWLD, a parallelized and generalized tool designed for the rapid genome-wide calculation of LD values, including conventional D/D′, [Formula: see text] , and (reduced) mutual information (MI and RMI) measures. LD between genetic variants within and across chromosomes can be rapidly computed and visualized in either an R package or a standalone C++ software package. To evaluate the accuracy and speed of LD calculation, we conducted comparisons using 4 real datasets. Interchromosomal LD patterns observed potentially reflect levels of selection intensity across different species. Both versions of GWLD, the R package (https://github.com/Rong-Zh/GWLD/tree/master/GWLD-R) and the standalone C++ software (https://github.com/Rong-Zh/GWLD/tree/master/GWLD-C%2B%2B), are freely available on GitHub.