Description Usage Arguments Value Examples

An algorithm for clustering of adjacent clusters

1 |

`ordr.vec` |
An (n by m) matrix of n measurements of m random variables (methylations). The columns are ordered. |

`thresh.dist` |
A distance threshold. Two neighboring clusters are merged to a single cluster if the distance between them is above thresh.dist. |

`which.clust` |
A vector of initial clusters assignments of the m variables. If it is not provided, it is taken that each site is a unique cluster. |

`location.vec` |
An m vector specifying the locations (e.g. chromosomal locations) of the variables measured in the matrix ordr.vec. |

`max.dist` |
Optional maximum length between neighboring variables permitting to cluster them together. |

`type` |
Type of clustering function. "single", "complete" or "average". |

`dist.type` |
Type of distance function "spearman", "pearson", or "euclid". |

An m vector of cluster assignments of the m ordered variables.

1 2 3 4 5 6 7 8 9 10 | ```
data(betas.7)
data(annot)
dat.7.ord <- order.betas.by.chrom.location(betas.7, annot = annot)
cluster.vec <- Acluster(ordr.vec = dat.7.ord$betas.by.chrom[[1]], thresh.dist = 0.2, location.vec = dat.7.ord$sites.locations.by.chrom[[1]]$Coordinate_36, max.dist = 1000, type = "average")
cluster.vec[1:10] ## sites 1 to 6 are clustered together, but 7,8,9 are singletons.
## alternatively, the function assign.to.clusters calls this function.
``` |

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