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Tools/Downloads
- Genes@Work is a software package to analyze patterns in gene array chip data.
You may run a demo of Genes@Work as a web-enabled applet by going to the applet page.
You may download a free, fully functional version by going to the download page.
For instructions to use this package, please see the users manual.
The unique pattern discovery algorithms in Genes@Work are described in the following paper:
A. Califano, G. Stolovitzky and Y. Tu. "Analysis of Gene Expression Microarrays for Phenotype Classification", Proceedings of the Annual Intelligent Systems in Molecular Biology (ISMB) 2000; 8:75-85 (2000). PDF
If you seek to use this software on your own server or for commercial purposes, please contact Gustavo Stolovitzky (gustavo@us.ibm.com).
- USE-Fold (uniform significance of expression-fold change) is a software package to evaluate statistical significance of gene expression fold changes based on our noise analysis.
This tool is available for download as part of the Genes@Work package above. USE-Fold can be run as a stand-alone tool or as integrated into the Genes@Work package. Note that the whole Genes@Work package must be downloaded to obtain the USE_Fold code. Please proceed to the Genes@Work download page to obtain the USE-Fold code.
The noise analysis and the USE-Fold algorithm are described in the following paper:
Yuhai Tu, G. Stolovitzky and U. Klein. "Quantitative noise analysis in gene expression microarray experiments", Y. Tu, G. Stolovitzky and U. Klein, Proceedings of National Academy of Sciences, 99(22), 14031-14036 (2002).
At this time, you may download the data (a set of replicate data and a set of test data) used in our paper for analyzing experimental noise in aligonucleotide-based microarrays. These two datasets are available:
If you seek to more information on this work, please contact Yuhai Tu (yuhai@us.ibm.com) or Gustavo Stolovitzky (gustavo@us.ibm.com).
- JUMPSTART is a tool that analyzes Massively Parallel Signature Sequencing (MPSS) data.
This tool is available for download at the JUMPSTART page.
For a description of this work, see:
G. Stolovitzky, A. Kundaje, G.A. Held, K. Duggar, C. Haudenschild, D. Zhou, T. Vasicek, K. Smith, A. Aderem and J. Roach, Statistical analysis of MPSS measurements: application to the study of LPS-activated macrophage gene expression, Proc. Natl. Acad. Sci. USA, 102 (5), 1402-1407 (2005). (Pubmed) (PNAS site)
If you seek to more information on this work, please contact Gustavo Stolovitzky (gustavo@us.ibm.com).
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