Research article
Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures
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* Corresponding author: Christos Sotiriou christos.sotiriou@bordet.be
1 Swiss Institute of Bioinformatics, 'Batiment Genopode', University of Lausanne, 1015 Lausanne, Switzerland
2 Translational Research and Medical Oncology Unit, Université Libre de Bruxelles, Institut Jules Bordet, 121 Boulevard de Waterloo, 1000 Brussels, Belgium
3 National Centers for Competence in Research, Molecular Oncology, Swiss Institute for Experimental Cancer Research, Ch. des Boveresses 155, 1066 Epalinges, Switzerland
4 DNA Array Facility, Center for Integrative Genomics, 'Batiment Genopode', University of Lausanne, 1015 Lausanne, Switzerland
5 Machine Learning Group, Université Libre de Bruxelles, boulevard du Triomphe, CP212, 1050 Bruxelles, Belgium
6 Institut de Mathématiques, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
Breast Cancer Research 2008, 10:R65 doi:10.1186/bcr2124
Published: 28 July 2008Additional files
Additional file 1:
Supplementary methods. Supplementary methods including the following sections: 'Probe annotation and gene matching', 'Preprocessing of expression values', 'Identifying coexpression modules', 'Module scores', 'Clustering and multimodality tests', 'Survival analysis', 'Cell-cycle periodicity' and 'Cross-platform applications of signatures'.
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Additional file 2:
Supplementary results. Supplementary Results including Supplementary Figures 1–5 and the results from the 'Combined prediction by pairs of signatures' (Supplementary Figure 6).
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Additional file 3:
ESR1, ERBB2 and proliferation coexpression modules. The spreadsheet describes the ESR1, ERBB2 and proliferation (AURKA) coexpression modules. The columns are described in the first lines starting by '#' in the text file.
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