This package provides a set of functions to test neighbor effects in genome-wide association studies. The neighbor effects are estimated using the Ising model of ferromagnetism. See Sato et al. (2021) for motivation and modeling.
Yasuhiro Sato (sato.yasuhiro.36c@kyoto-u.jp)
The flow of neighbor GWAS consists of two steps, (i) variation partitioning and (ii) association mapping.
In the first step, we compute proportion of phenotypic variation explained by neighbor effects, and estimate their effective area.
In the second step, we test neighbor effects, and map their association score on a genome.
In addition to standard GWAS inputs, spatial information of individuals is required to run these analyses.
See vignette("rNeighborGWAS") for how to use this package.
Sato Y, Yamamoto E, Shimizu KK, Nagano AJ (2021) Neighbor GWAS: incorporating neighbor genotypic identity into genome-wide association studies of field herbivory. Heredity 126(4):597-614. https://doi.org/10.1038/s41437-020-00401-w