snpgdsDrawTree: Draw a dendrogram

In SNPRelate: Parallel Computing Toolset for Relatedness and Principal Component Analysis of SNP Data

Description

To draw a dendrogram or the distribution of Z scores

Usage

snpgdsDrawTree(obj, clust.count=NULL, dend.idx=NULL,
    type=c("dendrogram", "z-score"), yaxis.height=TRUE, yaxis.kinship=TRUE,
    y.kinship.baseline=NaN, y.label.kinship=FALSE, outlier.n=NULL,
    shadow.col=c(rgb(0.5, 0.5, 0.5, 0.25), rgb(0.5, 0.5, 0.5, 0.05)),
    outlier.col=rgb(1, 0.50, 0.50, 0.5), leaflab="none",
    labels=NULL, y.label=0.2, ...)

Arguments

obj	an object returned by snpgdsCutTree
clust.count	the counts for clusters, drawing shadows
dend.idx	the index of sub tree, plot obj$dendrogram[[dend.idx]], or NULL for the whole tree
type	"dendrogram", draw a dendrogram; or "z-score", draw the distribution of Z score
yaxis.height	if TRUE, draw the left Y axis: height of tree
yaxis.kinship	if TRUE, draw the right Y axis: kinship coefficient
y.kinship.baseline	the baseline value of kinship; if NaN, it is the height of the first split from top in a dendrogram; only works when yaxis.kinship = TRUE
y.label.kinship	if TRUE, show 'PO/FS' etc on the right axis
outlier.n	the cluster with size less than or equal to outlier.n is considered as outliers; if NULL, let outlier.n = obj$outlier.n
shadow.col	two colors for shadow
outlier.col	the colors for outliers
leaflab	a string specifying how leaves are labeled. The default "perpendicular" write text vertically (by default). "textlike" writes text horizontally (in a rectangle), and "none" suppresses leaf labels.
labels	the legend for different regions
y.label	y positions of labels
...	Arguments to be passed to the method "plot(, ...)", such as graphical parameters.

Details

The details will be described in future.

Value

None.

Author(s)

Xiuwen Zheng

See Also

snpgdsCutTree

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"))

Example output

Loading required package: gdsfmt
SNPRelate -- supported by Streaming SIMD Extensions 2 (SSE2)
Individual dissimilarity analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Dissimilarity:    the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity:	Mon Mar 26 14:59:33 2018	0%
Dissimilarity:	Mon Mar 26 14:59:34 2018	100%
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.

SNPRelate documentation built on Nov. 8, 2020, 5:31 p.m.