Software
High-Throughput GoMiner, an 'industrial-strength' integrative gene ontology tool for interpretation of multiple-microarray experiments, with application to studies of Common Variable Immune Deficiency (CVID)
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* Corresponding author: John N Weinstein weinstein@dtpax2.ncifcrf.gov
- † Equal contributors
1 Genomics and Bioinformatics Group, Laboratory of Molecular Pharmacology, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
2 Metabolism Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
3 SRA International, 4300 Fair Lakes CT, Fairfax, VA 22033, USA
4 Advanced Biomedical Computing Center, National Cancer Institute at Frederick, SAIC Frederick, PO Box B, Frederick, MD, 21702, USA
5 Laboratory of Parasitic Disease, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
6 The Mount Sinai Medical Center, 1425 Madison Avenue, New York, NY 10029, USA
BMC Bioinformatics 2005, 6:168 doi:10.1186/1471-2105-6-168
Published: 5 July 2005Additional files
Additional File 1:
Stability of Estimates of the False Discovery Rate
Format: XLS Size: 1KB Download file
This file can be viewed with: Microsoft Excel Viewer
Additional File 2:
Expression Data
Format: XLS Size: 1MB Download file
This file can be viewed with: Microsoft Excel Viewer
Additional File 3:
Output Files Generated from High-Throughput GoMiner
Format: TAR Size: 2.8MB Download file
Additional File 6:
Summary Report
Format: XLS Size: 505KB Download file
This file can be viewed with: Microsoft Excel Viewer
Additional File 7:
Gene Category Report
Format: XLS Size: 225KB Download file
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Additional File 8:
CIM of Transcription Factors versus GO Categories
Format: PDF Size: 294KB Download file
This file can be viewed with: Adobe Acrobat Reader
Additional File 5:
Instructions for Generating the CIMs in the Manuscript
Format: PDF Size: 275KB Download file
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