Additional file 12: of The molecular landscape of premenopausal breast cancer

Supplementary methods. This file contains additional details of the analyses. (DOCX 36 kb

Additional file 7: of The molecular landscape of premenopausal breast cancer

PARADIGM analysis in The Cancer Genome Atlas (TCGA). Table S1. Pathways detected by gene set enrichment analysis (GSEA) with input of gene expression and copy number variation data for the PARADIGM algorithm. The nine columns correspond to the pathway name, size of the pathway, Enrichment score (ES) score, Normalized enrichment score (NES) score, nominal p value, false discovery rate (FDR) q value, Family-wise error rate (FWER) p value, and leading edge (typical GSEA output). Table S2. Pathways detected by GSEA with input of gene expression, copy number variation and methylation data for the PARADIGM algorithm. The nine columns correspond to the pathway name, the size of pathway, ES score, NES score, nominal p value, FDR q value, FWER p value, and leading edge (typical GSEA output). (XLSX 88 kb

Additional file 11: of The molecular landscape of premenopausal breast cancer

Gene list for clustering premenopausal (preM) estrogen receptor-positive (ER+) tumors. Table S1. Gene list selected by sparse k-means algorithm in The Cancer Genome Atlas (TCGA) data. Table S2. Genes selected based on TCGA data that are also in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) data for validation. Table S3. Fixed number of genes (n = 21), gene list being selected from sparse k-means in TCGA. Table S4. Gene list selected by semi-supervised algorithm in METABRIC. Table S5. Fixed number of genes (n = 21), gene list being selected by semi-supervised algorithm in TCGA. Table S6. Genes (n = 28) in the LumA cluster that are significantly different between clusters 1 and 3. (XLSX 37 kb