snp.pre.multiply {snpStats} | R Documentation

## Pre- or post-multiply a SnpMatrix object by a general matrix

### Description

These functions first standardize the input `SnpMatrix` in the same way as does the function `xxt`. The standardized matrix is then either pre-multiplied (`snp.pre.multiply`) or post-multiplied (`snp.post.multiply`) by a general matrix. Allele frequencies for standardizing the input SnpMatrix may be supplied but, otherwise, are calculated from the input SnpMatrix

### Usage

    snp.pre.multiply(snps, mat, frequency=NULL, uncertain = FALSE)
    snp.post.multiply(snps, mat, frequency=NULL, uncertain = FALSE)

### Arguments

`snps` | An object of class `"SnpMatrix"` or `"XSnpMatrix"`
`mat` | A general (numeric) matrix
`frequency` | A numeric vector giving the allele (relative) frequencies to be used for standardizing the columns of `snps`. If `NULL`, allele frequencies will be calculated internally. Frequencies should refer to the second (`B`) allele
`uncertain` | If `TRUE`, uncertain genotypes are replaced by posterior expectations. Otherwise these are treated as missing values

### Details

The two matrices must be conformant, as with standard matrix multiplication. The main use envisaged for these functions is the calculation of factor loadings in principal component analyses of large scale SNP data, and the application of these loadings to other datasets. The use of externally supplied allele frequencies for standardizing the input SnpMatrix is required when applying loadings calculated from one dataset to a different dataset

### Value

The resulting matrix product

### Author(s)

David Clayton dc208@cam.ac.uk

### See Also

`xxt`

### Examples

    ##--
    ##-- Calculate first two principal components and their loading, and verify
    ##--
    # Make a SnpMatrix with a small number of rows
    data(testdata)
    small <- Autosomes[1:20,]
    # Calculate the X.X-transpose matrix
    xx <- xxt(small, correct.for.missing=FALSE)
    # Calculate the first two principal components and corresponding eigenvalues
    eigvv <- eigen(xx, symmetric=TRUE)
    pc <- eigvv$vectors[,1:2]
    ev <- eigvv$values[1:2]
    # Calculate loadings for first two principal components
    Dinv <- diag(1/sqrt(ev))
    loadings <- snp.pre.multiply(small,  Dinv %*% t(pc))
    # Now apply loadings back to recalculate the principal components
    pc.again <- snp.post.multiply(small, t(loadings) %*% Dinv)
    print(cbind(pc, pc.again))

[Package snpStats version 1.30.0 Index]