snp.pre {snpMatrix} | R Documentation |
These functions first standardize the input snp.matrix
in the
same way as does the function xxt
. The standardized
matrix is then either pre-multiplied (snp.pre
) or
post-multiplied (snp.post
) by a general matrix. Allele
frequencies for standardizing the input snp.matrix may be supplied
but, otherwise, are calculated from the input snp.matrix
snp.pre(snps, mat, frequency=NULL) snp.post(snps, mat, frequency=NULL)
snps |
An object of class "snp.matrix" or "X.snp.matrix" |
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
|
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 snp.matrix is required when applying loadings calculated from one dataset to a different dataset
The resulting matrix product
David Clayton david.clayton@cimr.cam.ac.uk
##-- ##-- Calculate first two principal components and their loading, and verify ##-- # Make a snp.matrix 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(small, Dinv %*% t(pc)) # Now apply loadings back to recalculate the principal components pc.again <- snp.post(small, t(loadings) %*% Dinv) print(cbind(pc, pc.again))