Fig. 3
Identification of consensus clusters by m6A regulators associated with the clinicopathological characteristic and pathway. A Consensus clustering cumulative distribution function (CDF) diagram with a clustering number from k = 2 to k = 9. B Consensus clustering matrix for k = 2, displaying the clustering stability using 1000 iterations of hierarchical clustering. C Principal component analysis (PCA) for the transcriptome profiles of two consensus clusters. D Kaplan–Meier curves for patients with BCa. Patients in cluster 1 were marked with blue, while those in cluster 2 were marked with red. E Heatmap and clinicopathologic features of the two clusters classified by the m6A regulators consensus expression. The m6A cluster, N status, M status, T status, tumor stage, tumor grade, gender, and age were used as patient annotations. Red represents the high expression of m6A regulators and blue represents the low expression. F–G Gene set variation analysis (GSVA) enrichment analysis showed the status of biological pathways between the two clusters. The volcano plot was used to visualize these biological processes. Red dots represents the activated pathways and green dots represents the inhibited pathways, logFC set as 0.1, and P value set as 0.05 (F), and the heatmap was used to visualize these biological processes and red represented activated pathways and green represented inhibited pathways (G)