snpgdsPCACorr {SNPRelate} | R Documentation

## PC-correlated SNPs in principal component analysis

### Description

To calculate the SNP correlations between eigenvactors and SNP genotypes

### Usage

    snpgdsPCACorr(pcaobj, gdsobj, snp.id=NULL, eig.which=NULL, num.thread=1L,
        with.id=TRUE, outgds=NULL, verbose=TRUE)

### Arguments

`pcaobj` | a `snpgdsPCAClass` object returned from the function snpgdsPCA, a `snpgdsEigMixClass` from snpgdsEIGMIX, or an eigenvector matrix with row names (sample id)
`gdsobj` | an object of class `SNPGDSFileClass`, a SNP GDS file
`snp.id` | a vector of snp id specifying selected SNPs; if NULL, all SNPs are used
`eig.which` | a vector of integers, to specify which eigenvectors to be used
`num.thread` | the number of (CPU) cores used; if `NA`, detect the number of cores automatically
`with.id` | if `TRUE`, the returned value with `sample.id` and `sample.id`
`outgds` | `NULL` or a character of file name for exporting correlations to a GDS file, see details
`verbose` | if TRUE, show information

### Details

If an output file name is specified via `outgds`, "sample.id", "snp.id" and "correlation" will be stored in the GDS file. The GDS node "correlation" is a matrix of correlation coefficients, and it is stored with the format of packed real number ("packedreal16" preserving 4 digits, 0.0001 is the smallest number greater zero, see add.gdsn).

### Value

Return a list if `outgds=NULL`,

`sample.id` | the sample ids used in the analysis
`snp.id` | the SNP ids used in the analysis
`snpcorr` | a matrix of correlation coefficients, "# of eigenvectors" x "# of SNPs"

### Author(s)

Xiuwen Zheng

### References

Patterson N, Price AL, Reich D (2006) Population structure and eigenanalysis. PLoS Genetics 2:e190.

### See Also

`snpgdsPCA`, `snpgdsPCASampLoading`, `snpgdsPCASNPLoading`

### Examples

    # open an example dataset (HapMap)
    genofile <- snpgdsOpen(snpgdsExampleFileName())
    # get chromosome index
    chr <- read.gdsn(index.gdsn(genofile, "snp.chromosome"))

    pca <- snpgdsPCA(genofile)
    cr <- snpgdsPCACorr(pca, genofile, eig.which=1:4)
    plot(abs(cr$snpcorr[3,]), xlab="SNP Index", ylab="PC 3", col=chr)

    # output to a gds file if limited memory
    snpgdsPCACorr(pca, genofile, eig.which=1:4, outgds="test.gds")

    (f <- openfn.gds("test.gds"))
    m <- read.gdsn(index.gdsn(f, "correlation"))
    closefn.gds(f)

    # check
    summary(c(m - cr$snpcorr))  # should < 1e-4

    # close the file
    snpgdsClose(genofile)

    # delete the temporary file
    unlink("test.gds", force=TRUE)

[Package SNPRelate version 1.26.0 Index]