Elucidating the Altered Transcriptional Programs in Breast Cancer using Independent Component Analysis
Figure 4
Heatmaps of Association of Pathways and Regulatory Modules with Breast Cancer Phenotypes
For three phenotypes (ER, Grade, Outcome), we show heatmaps of association between phenotypes and selected pathways (A) and selected regulatory motifs (B), as revealed by the four ICA algorithms across the four major breast cancer cohorts. For phenotypes, we used a p-value threshold of 0.05 to establish whether an ICA component was associated with that phenotype. For pathways and regulatory modules, we used the Benjamini corrected p-values as before. For each cohort, we then counted the number of ICA algorithms that found a component linking a phenotype with a pathway/regulatory module, which was colour-coded as 4 (dark red), 3 (red), 2 or 1 (pink), and 0 (white). For Wang's cohort, grade information was unavailable and is colour-coded as grey.