SNPRelate (version 1.6.4)

snpgdsDiss: Individual dissimilarity analysis

Description

Calculate the individual dissimilarities for each pair of individuals.

Usage

snpgdsDiss(gdsobj, sample.id=NULL, snp.id=NULL, autosome.only=TRUE, remove.monosnp=TRUE, maf=NaN, missing.rate=NaN, num.thread=1, verbose=TRUE)

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 "

num.thread

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

verbose

if TRUE, show information

Value

Return a class "snpgdsDissClass":

sample.id

the sample ids used in the analysis

snp.id

the SNP ids used in the analysis

diss

a matrix of individual dissimilarity

Details

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

The details will be described in future.

References

Zheng, Xiuwen. 2013. Statistical Prediction of HLA Alleles and Relatedness Analysis in Genome-Wide Association Studies. PhD dissertation, the department of Biostatistics, University of Washington.

Weir BS, Zheng X. SNPs and SNVs in Forensic Science. 2015. Forensic Science International: Genetics Supplement Series.

See Also

snpgdsHCluster

Examples

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

pop.group <- as.factor(read.gdsn(index.gdsn(
    genofile, "sample.annot/pop.group")))
pop.level <- levels(pop.group)

diss <- snpgdsDiss(genofile)
hc <- snpgdsHCluster(diss)

# close the genotype file
snpgdsClose(genofile)


# split
set.seed(100)
rv <- snpgdsCutTree(hc, label.H=TRUE, label.Z=TRUE)

# draw dendrogram
snpgdsDrawTree(rv, main="HapMap Phase II",
    edgePar=list(col=rgb(0.5,0.5,0.5, 0.75), t.col="black"))