snpgdsDrawTree {SNPRelate} | 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

### 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"))

[Package SNPRelate version 1.26.0 Index]