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Tmm: Analysis of multiple microarray data sets
TMM is being phased out in favor of our new resource, Gemma.
Go directly to the Tmm web interface.
Tmm is an experimental system for exploring the coexpression of genes based on microarray data. This page contains links to supplementary data to our paper "Coexpression analysis of human genes across many microarray data sets". You can read the abstract or download a PDF.
For a description of the data sets we used, click here. Our thanks to those who have made their data available.
For documentation of the web interface, look here
May 9 2004: The database has been updated and now contains many more mouse data sets. More updates will be available soon, in particular to the metadata, which is incomplete for many of the sets. Because of this update, the online version of the database is no longer identical to the one used in our paper and might yield slightly different results for the same queries. This is because we are still experimenting with the methods used to select coexpression links.
In the coming months we will be adding additional datasets and tools.
Figure 4 in the paper makes use of matrix2png, a simple piece of software we use to make matrix visualizations. Clustering was performed using Gavin Sherlocks "Xcluster". We also used our own implementation of Bader and Hogue's "MCODE" (Those interested in our MCODE implementation should contact us). Figure 5 used Pajek, a network visualization and analysis package. Our gene annotations, which were used to determine what genes were on what microarrays, are all derived from our Ermine database, which has its own simple web interface. Much of the microarray data was obtained from the Stanford or NCBI databases. We also made heavy use of the Gene Ontology, LocusLink, Unigene and Swissprot databases.
Supplemental data and figures for the paper
Supplementary tables for the paper
The following files are available for download. All are plain ASCII tab-delimited text. Most of the files have been compressed (tar'ed and gzip'ed) and must be unpacked before viewing. Many of the files can be opened in Excel, but some of them are quite large and are intended for use in automated analyses. Each file has a header that explains the columns. Note that in several files positive and negative correlations are counted separately, typically denoted by "+" and "-" respectively.
|Paul Pavlidis. Last modified: Tue Feb 22 11:38:22 EST 2005|