bed_projectSelfPCA: Projecting PCA
In bigsnpr: Analysis of Massive SNP Arrays

bed_projectSelfPCA

R Documentation

Projecting PCA

Projecting PCA using individuals from one dataset to other individuals from the same dataset.

bed_projectSelfPCA(
  obj.svd,
  obj.bed,
  ind.row,
  ind.col = attr(obj.svd, "subset"),
  ncores = 1
)

`obj.svd`	List with `v`, `d`, `center` and `scale`. Typically the an object of type "big_SVD".
`obj.bed`	Object of type bed, which is the mapping of the bed file of the data containing both the individuals that were used to compute the PCA and the other individuals to be projected.
`ind.row`	Rows (individuals) to be projected.
`ind.col`	Columns that were used for computing PCA. If bed_autoSVD was used, then `attr(obj.svd, "subset")` is automatically used by default. Otherwise (e.g. if bed_randomSVD was used), you have to pass `ind.col`.
`ncores`	Number of cores used. Default doesn't use parallelism. You may use `bigstatsr::nb_cores()`.

A list of 3 elements:

⁠$obj.svd.ref⁠: big_SVD object computed from reference data.
⁠$simple_proj⁠: simple projection of new data into space of reference PCA.
⁠$OADP_proj⁠: Online Augmentation, Decomposition, and Procrustes (OADP) projection of new data into space of reference PCA.