snpgdsAdmixProp {SNPRelate} | R Documentation

## Estimate ancestral proportions from the eigen-analysis

### Description

Estimate ancestral (admixture) proportions based on the eigen-analysis.

### Usage

    snpgdsAdmixProp(eigobj, groups, bound=FALSE)

### Arguments

`eigobj` | an object of `snpgdsEigMixClass` from `snpgdsEIGMIX`, or an object of `snpgdsPCAClass` from `snpgdsPCA`
`groups` | a list of sample IDs, such like `groups = list( CEU = c("NA0101", "NA1022", ...), YRI = c("NAxxxx", ...), Asia = c("NA1234", ...))`
`bound` | if `TRUE`, the estimates are bounded so that no component < 0 or > 1, and the sum of proportions is one

### Details

The minor allele frequency and missing rate for each SNP passed in `snp.id` are calculated over all the samples in `sample.id`.

### Value

Return a `snpgdsEigMixClass` object, and it is a list:

`sample.id` | the sample ids used in the analysis
`snp.id` | the SNP ids used in the analysis
`eigenval` | eigenvalues
`eigenvect` | eigenvactors, "# of samples" x "eigen.cnt"
`ibdmat` | the IBD matrix

### Author(s)

Xiuwen Zheng

### References

Zheng X, Weir BS. Eigenanalysis on SNP Data with an Interpretation of Identity by Descent. Theoretical Population Biology. 2015 Oct 23. pii: S0040-5809(15)00089-1. doi: 10.1016/j.tpb.2015.09.004. [Epub ahead of print]

### See Also

`snpgdsEIGMIX`, `snpgdsPCA`, `snpgdsAdmixPlot`

### Examples

    # open an example dataset (HapMap)
    genofile <- snpgdsOpen(snpgdsExampleFileName())

    # get population information
    #   or pop_code <- scan("pop.txt", what=character())
    #   if it is stored in a text file "pop.txt"
    pop_code <- read.gdsn(index.gdsn(genofile, "sample.annot/pop.group"))

    # get sample id
    samp.id <- read.gdsn(index.gdsn(genofile, "sample.id"))

    # run eigen-analysis
    RV <- snpgdsEIGMIX(genofile)

    # eigenvalues
    RV$eigenval

    # make a data.frame
    tab <- data.frame(sample.id = samp.id, pop = factor(pop_code),
        EV1 = RV$eigenvect[,1],    # the first eigenvector
        EV2 = RV$eigenvect[,2],    # the second eigenvector
        stringsAsFactors = FALSE)
    head(tab)

    # draw
    plot(tab$EV2, tab$EV1, col=as.integer(tab$pop),
        xlab="eigenvector 2", ylab="eigenvector 1")
    legend("topleft", legend=levels(tab$pop), pch="o", col=1:4)

    # define groups
    groups <- list(CEU = samp.id[pop_code == "CEU"],
        YRI = samp.id[pop_code == "YRI"],
        CHB = samp.id[is.element(pop_code, c("HCB", "JPT"))])

    prop <- snpgdsAdmixProp(RV, groups=groups)

    # draw
    plot(prop[, "YRI"], prop[, "CEU"], col=as.integer(tab$pop),
        xlab = "Admixture Proportion from YRI",
        ylab = "Admixture Proportion from CEU")
    abline(v=0, col="gray25", lty=2)
    abline(h=0, col="gray25", lty=2)
    abline(a=1, b=-1, col="gray25", lty=2)
    legend("topright", legend=levels(tab$pop), pch="o", col=1:4)

    # draw
    snpgdsAdmixPlot(prop, group=pop_code)

    # close the genotype file
    snpgdsClose(genofile)

[Package SNPRelate version 1.26.0 Index]