snpgdsEIGMIX {SNPRelate}R Documentation

Eigen-analysis on SNP genotype data

Description

Eigen-analysis on IBD matrix based SNP genotypes.

Usage

snpgdsEIGMIX(gdsobj, sample.id=NULL, snp.id=NULL, autosome.only=TRUE,
    remove.monosnp=TRUE, maf=NaN, missing.rate=NaN, num.thread=1L,
    eigen.cnt=32L, diagadj=TRUE, ibdmat=FALSE, verbose=TRUE)
## S3 method for class 'snpgdsEigMixClass'
plot(x, eig=c(1L,2L), ...)

Arguments

gdsobj

an object of class SNPGDSFileClass, a SNP GDS file

sample.id

a vector of sample id specifying selected samples; if NULL, all samples are used

snp.id

a vector of snp id specifying selected SNPs; if NULL, all SNPs are used

autosome.only

if TRUE, use autosomal SNPs only; if it is a numeric or character value, keep SNPs according to the specified chromosome

remove.monosnp

if TRUE, remove monomorphic SNPs

maf

to use the SNPs with ">= maf" only; if NaN, no MAF threshold

missing.rate

to use the SNPs with "<= missing.rate" only; if NaN, no missing threshold

num.thread

the number of (CPU) cores used; if NA, detect the number of cores automatically

eigen.cnt

output the number of eigenvectors; if eigen.cnt < 0, returns all eigenvectors; if eigen.cnt==0, no eigen calculation

diagadj

TRUE for diagonal adjustment by default

ibdmat

if TRUE, returns the IBD matrix

verbose

if TRUE, show information

x

a snpgdsEigMixClass object

eig

indices of eigenvectors, like 1:2 or 1:4

...

the arguments passed to or from other methods, like pch, col

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"

afreq

allele frequencies

ibd

the IBD matrix when ibdmat=TRUE

diagadj

the argument diagadj

Author(s)

Xiuwen Zheng

References

Zheng X, Weir BS. Eigenanalysis on SNP Data with an Interpretation of Identity by Descent. Theoretical Population Biology. 2016 Feb;107:65-76. doi: 10.1016/j.tpb.2015.09.004

See Also

snpgdsAdmixProp, snpgdsAdmixPlot, snpgdsPCA, snpgdsPCASNPLoading, snpgdsPCASampLoading

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)


# close the genotype file
snpgdsClose(genofile)

[Package SNPRelate version 1.10.2 Index]