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Fig. 1 | Breast Cancer Research

Fig. 1

From: Detecting gene signature activation in breast cancer in an absolute, single-patient manner

Fig. 1

Instability of current pathway activation inference tools and example application of the region of independence (ROI). a Absolute difference between the score obtained from a specific pathway activation tool (gene set variation analysis (GSVA), single sample gene set enrichment analysis (ssGSEA), zscore, or pathway level analysis of gene expression (PLAGE)) using all patients from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset, and the score obtained when this dataset is restricted to either estrogen receptor (ER)-negative (ER-) samples (left) or ER-positive (ER+) samples (right). b Heatmap depicts the ROI induced over the rank-sum-base ordering of patients in the METABRIC dataset using the estrogen activation gene signature from Doane et al. with the probability (1) and cumulative distribution function (2) for the random trials, in addition to the final assignments (3) into low, high and independent regions (defined as the 95% CI of the index of the random trials). c Distribution of the low, independent and high assignments defined by the ROI95 in the function of the clinical subtypes (defined by ER and human epidermal growth factor receptor 2 (HER2) status). d Class assignments defined by the ROI95 are prognostic with 5 years survival (log-rank test P < 0.00001)

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