Skip to content

Python translation of the hybrid dynamicTreeCut method as created by Peter Langfelder and Bin Zhang.

Notifications You must be signed in to change notification settings

kylessmith/dynamicTreeCut

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Stars PyPIDownloads PyPI Build Status Coffee

Python translation of the hybrid dynamicTreeCut method created by Peter Langfelder and Bin Zhang.

dynamicTreeCut was originally published by in Bioinformatics:
Langfelder P, Zhang B, Horvath S (2007) Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R. Bioinformatics 2008 24(5):719-720

dynamicTreeCut R code is distributed under the GPL-3 License and original sources should be cited.

dynamicTreeCut contains methods for detection of clusters in hierarchical clustering dendrograms. NOTE: though the clusters match the R output, the cluster names are shuffled

Installing

To install, it's best to create an environment after installing and downloading the Anaconda Python Distribution

conda env create --file environment.yml

PyPI install, presuming you have all its requirements (numpy and scipy) installed:

pip install dynamicTreeCut

Importation

>>> from dynamicTreeCut import cutreeHybrid
>>> from scipy.spatial.distance import pdist
>>> import numpy as np
>>> from scipy.cluster.hierarchy import linkage
>>> d = np.transpose(np.arange(1,10001).reshape(100,100))
>>> distances = pdist(d, "euclidean")
>>> link = linkage(distances, "average")
>>> clusters = cutreeHybrid(link, distances)
..cutHeight not given, setting it to 495.1  ===>  99% of the (truncated) height range in dendro.
..done.
>>> clusters["labels"]
[2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3
 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 1 1 1 1 1 1 1
 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]

Compared to R:

> library(dynamicTreeCut)
> d = matrix(1:10000, 100)
> distances <- dist(d, method="euclidean")
> dendro <- hclust(distances, method="average")
> clusters <- cutreeDynamic(dendro, distM=as.matrix(distances))
  ..cutHeight not given, setting it to 495  ===>  99% of the (truncated) height range in dendro.
  ..done.
> clusters
  [1] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3
  [38] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 1 1 1 1 1 1 1
  [75] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

Installation

If you dont already have numpy and scipy installed, it is best to download Anaconda, a python distribution that has them included.

https://continuum.io/downloads

Dependencies can be installed by:

pip install -r requirements.txt

License

dynamicTreeCut is available under the GPL-3 License

About

Python translation of the hybrid dynamicTreeCut method as created by Peter Langfelder and Bin Zhang.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages