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Last data update: 2014.03.03

R: Draw a dendrogram

snpgdsDrawTree

R Documentation

Draw a dendrogram

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

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"))

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(SNPRelate)
Loading required package: gdsfmt
SNPRelate -- supported by Streaming SIMD Extensions 2 (SSE2)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/SNPRelate/snpgdsDrawTree.Rd_%03d_medium.png", width=480, height=480)
> ### Name: snpgdsDrawTree
> ### Title: Draw a dendrogram
> ### Aliases: snpgdsDrawTree
> ### Keywords: GDS GWAS
> 
> ### ** 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)
Individual dissimilarity analysis on SNP genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, < MAF: NaN, or > missing rate: NaN)
Working space: 279 samples, 8722 SNPs
	using 1 (CPU) core
Dissimilarity:	the sum of all selected genotypes (0, 1 and 2) = 2446510
Dissimilarity:	Wed Jul  6 05:34:35 2016	0%
Dissimilarity:	Wed Jul  6 05:34:36 2016	100%
> hc <- snpgdsHCluster(diss)
> 
> # close the genotype file
> snpgdsClose(genofile)
> 
> 
> # split
> set.seed(100)
> rv <- snpgdsCutTree(hc, label.H=TRUE, label.Z=TRUE)
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.
> 
> # draw dendrogram
> snpgdsDrawTree(rv, main="HapMap Phase II",
+     edgePar=list(col=rgb(0.5,0.5,0.5, 0.75), t.col="black"))
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>

Draw a dendrogram

Description

Usage

Arguments

Details

Value

Author(s)

See Also

Examples

Results