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<h1> CompClust </h1>
<br>
<a href="/compclust/">Home</a>
| <a href="/compclust/intro.shtml">Introduction</a>
| <a href="/compclust/docs.shtml">Documentation</a>
| <a href="/compclust/download.shtml">Downloads</a>
| <a href="/compclust/mail_contact.shtml">Mailing
List & Contact</a> | <a href="/compclust/links.shtml">Links</a>
| <a href="/compclust/refs.shtml">References</a><br>
<br>
<h2>News</h2>
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<h4>2005 Dec 14</h4>
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<p>The latest version of CompClust 1.2 is now available.</p>
<p>Version 1.2 Includes a substantial revision of our
principal component analysis (PCA) interpretation software
(publication forthcoming).
</p>
<p>
Interested researchers can use our web-based application,
<a href="http://woldlab.caltech.edu/publications/pca-bmc-2005/demo/">CompClustWeb</a>
to interactively review the results of our analysis of the
GNF human <a href=http://symatlas.gnf.org/SymAtlas>GNF
human gene expression data</a> from the SymAtlas web site
at the Genomics Institute of the Novartis Research
Foundation.
</p>
<p>
You can <a href="/compclust/download.shtml">download one
of the CompClust packages</a> to futher explore CompClust.
We have a new tutorial [ <a
href="http://woldlab.caltech.edu/compclust/pca_interpretation_tutorial">html</a>
| <a
href="http://woldlab.caltech.edu/compclust/pca_interpretation_tutorial.pdf">pdf</a>
] that describes how to use the CompClust programming API
to perform a PCA interpretation analysis of a dataset.<br><br>
</p>
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<h4>2005 Jun 22</h4>
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<p>Beta version of compclust 1.1 made available</p>
<p>Version 1.1 focuses on making installation from the python
source much simpler and far more robust.
</p>
<p>New features consist of shipping the clustering algorithm
binaries, installing those binaries when doing
<code>python setup.py install</code> and finding them after
having installed compclust.
</p>
<p>
You can get the source
<a href="compclust-1.1.zip">compclust-1.1.zip</a>
If there are any problems please let us know. send email to
user compclust with a domain woldlab.caltech.edu
</p>
<p>
Upcoming plans include fixing rendering of the TrajectorySummary
plot which gets crowded as the number of clusters increases.
More work on trying to opensource the C code, switching to Quixote2,
simpler data loading tools, and a mysterious new pca analysis tool.
</p>
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<h4>2005 May 27</h4>
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<p>CompClust mailing
list now available</p>
<p>If you're using
CompClust please <a
href="http://woldlab.caltech.edu/cgi-bin/mailman/listinfo/compclust">
sign up</a> so we can notify you of
future releases and discuss what
features to develop next. </p>
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<h4>2005 May 16</h4>
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<p>CompClust 1.0
release (previously known as 0.2.1)<br>
CompClustTk 1.0 release (previously known as 0.2.16)<br>
CompClustTk tutorial updated</p>
<p> In the new
release, CompClustWeb, has made significant
progress toward being able to duplicate the functionality of
CompClustTk. </p>
<p> 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). </p>
<p> 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. </p>
<p> 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. </p>
<p> Currently the
CompClustTk version also has better
documentation. </p>
<p> 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. </p>
<p> 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).<br>
</p>
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<h4>2004Oct22</h4>
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<ul>
<li>Added
information about CompClust, CompClustTk, and
CompClustWeb to Introduction section.</li>
<li>Improved
installation documentation.</li>
<li>Added binaries
for Windows algorithms for those who
wish to install the CompClust Python package. (Already included in
CompClustTk Windows Installer.)</li>
</ul>
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<h4>2004May12</h4>
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<li>CompClustTk
v0.2.12 Released</li>
<li>CompClust v0.2
Released</li>
</ul>
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