chooseClusters {beadarray} | R Documentation

## Choose Clusters

### Description

Find large clusters of beads.

### Usage

    chooseClusters(IDs, neighbours, cutoff = 8)

### Arguments

`IDs` | IDs of beads to be clustered.
`neighbours` | A Neighbours matrix - obtained from `generateNeighbours`.
`cutoff` | Integer - threshold for the minimum size a cluster must be.

### Details

This function will find which beads are in large clusters. Using a flood fill algorithm, it finds clusters of beads, determines the size of each, and then returns only the beads in clusters of size greater than `cutoff`. It is primarily used in `BASHCompact` and `BASHDiffuse`.

### Value

Vector of bead IDs. (This will be a subset of the argument `IDs`)

### Author(s)

Jonathan Cairns

### See Also

`BASHCompact`, `BASHDiffuse`, `closeImage`

### Examples

    data(BLData)
    neighbours <- generateNeighbours(BLData,1)
    o <- findAllOutliers(BLData,1,log = TRUE)
    ##clusters8 <- chooseClusters(o, neighbours)
    ##clusters12 <- chooseClusters(o, neighbours, cutoff = 12) ## only ##larger clusters

    ##x11()
    ##plotBeadLocations(BLData,array=1,BeadIDs = clusters8, pch = ".")

[Package beadarray version 1.12.1 Index]