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Fig. 1 | Genome Medicine

Fig. 1

From: Crosstalk between microRNA expression and DNA methylation drives the hormone-dependent phenotype of breast cancer

Fig. 1

Identification of miRNA-methylation Quantitative Trait Loci (mimQTL) clusters and corresponding annotation. a Heatmap showing hierarchical clustering of the 89,118 significant mimQTLs found in both the Oslo2 and TCGA cohorts. miRNAs are shown in columns and CpGs in rows. In the heatmap, blue color indicates a negative correlation and red color indicates a positive correlation between miRNA expression and CpG methylation. Three main miRNA clusters (cluster A, B, and C) and two main CpG clusters (cluster 1 and 2) were identified. b–d Barplots showing the top five most enriched pathways for genes co-expressed (miRNA-mRNA expression Spearman correlation > 0.4) with the miRNAs of cluster A (b), B (c), and C (d). The x-axis show the − log10(p value) of the pathway enrichment obtained from Enrichr [33]. Bars are color-coded according to the associated miRNA cluster. e–g Results from fitting generalized linear models (GLM) to model miRNA expression as a multivariate function of lymphocyte infiltration (obtained by Nanodissect [34]), fibroblast infiltration (obtained by xCell [35]), and ESR1 mRNA expression. The GLM coefficients are depicted with 95% confidence intervals for each of the miRNAs with the highest number of CpG associations in each cluster. Asterisks (***) denote a p value < 0.001 and “ns” denotes not significant (p value > 0.05)

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