bigsnpr: snp_pcadapt – R documentation

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snp_pcadapt

Outlier detection

Description

Method to detect genetic markers involved in biological adaptation. This provides a statistical tool for outlier detection based on Principal Component Analysis. This corresponds to the statistic based on mahalanobis distance, as implemented in package pcadapt.

Usage

snp_pcadapt(
  G,
  U.row,
  ind.row = rows_along(G),
  ind.col = cols_along(G),
  ncores = 1
)

bed_pcadapt(
  obj.bed,
  U.row,
  ind.row = rows_along(obj.bed),
  ind.col = cols_along(obj.bed),
  ncores = 1
)

Arguments

`G`	A FBM.code256 (typically `<bigSNP>$genotypes`). You shouldn't have missing values. Also, remember to do quality control, e.g. some algorithms in this package won't work if you use SNPs with 0 MAF.
`U.row`	Left singular vectors (not scores, U^T U = I) corresponding to `ind.row`.
`ind.row`	An optional vector of the row indices (individuals) that are used. If not specified, all rows are used. Don't use negative indices.
`ind.col`	An optional vector of the column indices (SNPs) that are used. If not specified, all columns are used. Don't use negative indices.
`ncores`	Number of cores used. Default doesn't use parallelism. You may use nb_cores.
`obj.bed`	Object of type bed, which is the mapping of some bed file. Use `obj.bed <- bed(bedfile)` to get this object.

Value

An object of classes mhtest and data.frame returning one score by SNP. See methods(class = "mhtest").

References

Luu, K., Bazin, E., & Blum, M. G. (2017). pcadapt: an R package to perform genome scans for selection based on principal component analysis. Molecular ecology resources, 17(1), 67-77.

Examples

test <- snp_attachExtdata()
G <- test$genotypes
obj.svd <- big_SVD(G, fun.scaling = snp_scaleBinom(), k = 10)
plot(obj.svd) # there seems to be 3 "significant" components
pcadapt <- snp_pcadapt(G, obj.svd$u[, 1:3])
snp_qq(pcadapt)

bigsnpr

Analysis of Massive SNP Arrays

v1.10.8

GPL-3

Authors

Florian Privé [aut, cre], Michael Blum [ths], Hugues Aschard [ths], Bjarni Jóhann Vilhjálmsson [ths]

Initial release

2022-07-05