Implements a constrained version of hierarchical agglomerative clustering, in which each observation is associated to a position, and only adjacent clusters can be merged. Typical application fields in bioinformatics include Genome-Wide Association Studies or Hi-C data analysis, where the similarity between items is a decreasing function of their genomic distance. Taking advantage of this feature, the implemented algorithm is time and memory efficient. This algorithm is described in Chapter 4 of Alia Dehman (2015) <https://hal.archives-ouvertes.fr/tel-01288568v1>.
|Author||Christophe Ambroise [aut], Shubham Chaturvedi [aut], Alia Dehman [aut], Michel Koskas [aut], Pierre Neuvial [aut, cre], Guillem Rigaill [aut], Nathalie Vialaneix [aut]|
|Maintainer||Pierre Neuvial <[email protected]>|
|Package repository||View on CRAN|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.