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2005 May 27

CompClust mailing list now available

If you're using CompClust please sign up so we can notify you of future releases and discuss what features to develop next.

2005 May 16

CompClust 1.0 release (previously known as 0.2.1)
CompClustTk 1.0 release (previously known as 0.2.16)
CompClustTk tutorial updated

In the new release, CompClustWeb, has made significant progress toward being able to duplicate the functionality of CompClustTk.

CompClustWeb as one might guess provides access to the core CompClust functionality from within a web browser. It can be used either from within an scgi compliant server or using one of the python webservers (like medusa or twisted).

CompClustWeb supports loading multiple datasets simultaneously, and has support for running the MultiRun cross validated clustering algorithm. CompClustTk was our first GUI toolkit and provides a significantly more interactive PCA browser, additionally accessing the IPython command line to perform tasks such as log2 transforming a dataset is much easier from within the TK version.

When run with one of the python webservers it is possible to access the datasets from within IPython although it is currently undocumented how one might go abou taking advantage of this.

Currently the CompClustTk version also has better documentation.

We hope to create a new release soon that will be the last supported version for CompClustTk that includes the ability to run MultiRun. We plan on making CompClustWeb our primary GUI environment in future releases.

Internally the methods for accessing wrapper parameters have gone through some significant changes and are hopefully much easier to use if one is writing CompClust scripts. (If you're interested the test cases contain examples of how these new features work).


  • Added information about CompClust, CompClustTk, and CompClustWeb to Introduction section.
  • Improved installation documentation.
  • Added binaries for Windows algorithms for those who wish to install the CompClust Python package. (Already included in CompClustTk Windows Installer.)


  • CompClustTk v0.2.12 Released
  • CompClust v0.2 Released


CompClust is a python package written using the pyMLX and IPlot APIs. It provides software tools to explore and quantify relationships between clustering results. Its development has been largely built around needs of microarray data analysis but could be easily used in other domains.

Briefly pyMLX provides an provides for efficient and convenient execution of many clustering algorithms using a extendable library of algorithms. It also provides many-to-many linkages between data features and annotations (such as cluster labels, gene names, gene ontology information, etc.) This linkages are are persistent through data manipulations. IPlot provides an abstraction of the plotting process in which any arbitrary feature or derived feature of the data can be projected onto any feature of the plot, including the X,Y coordinates of points, marker symbol, marker size, maker/line color, etc. These plots are intrinsically linked to the dataset, the View and the Labeling classes found within pyMLX.

CompClust is currently available in two forms and soon we will be adding an additional form.

  • CompClust Python Package - Described above.
  • CompClustTk - A GUI for providing a fully interactive environment for loading, clustering and visualizing integrated bioinformatics datasets. This package is built on top of the CompClust python package, and is designed to make it easy for a biologist to easily begin to use CompClust. It doesn't expose all of CompClust's advanced features, but it is a good starting point for someone who is new to CompClust. Easy to use installer available for Windows.
  • CompClustWeb - Inspired by CompClustTk, but designed as web application so individual users don't have to go through the process of installing a local client. It should be useable by anyone who has a modern web browser. Coming Soon



CompClustTk - Easy to use Windows Installer

CompClust Python Package Installation



The Python language's website. Plenty of good resources regarding python
IPython provides an enhanced interactive shell with tab-completion, object introspection, online help, history and many other nice features. I highly recommend using IPython, here are compClust specific IPython configuration files: Numeric/Scientific python and compClust. Save these files into your IPYTHONDIR and then start ipython with the compClust profile by using the -p option: ipython -p compClust

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