Additional file 2: of Refinement of breast cancer molecular classification by miRNA expression profiles

Figure S1. Boxplot summarising sequencing statistics including total purity-filtered reads, uniquely aligned reads, multimapping reads, unaligned reads and reads that were removed due to a very short insert size (< 14 nt) across all libraries. Figure S2. Boxplot summary of the insert size on top for the aligned reads and summary of the composition based on RNA class. Figure S3. Cumulative counts of expressed miRNAs in the expression interval − 5 to 20 log2 counts per million reads (cpm) show that all sequenced libraries have a high and similar miRNA profile complexity. The intervals are spaced by 0.5 log2 cpm. The individual samples are plotted in grey and the mean sample is plotted in black. Figure S4. Plots from consensusclustering analysis. The number of k clusters (k = 3) was identified from the delta area plot. As observed the increase in consensus with the number of clusters. The increase in consensus is low for k = 4 and therefore k = 3 was used. Figure S5. Expression pileups for mir-2115 and mir-7158 from miRCarta. Figure S6. Clustering of TCGA breast cancer using the miRNAs identified in our analysis. Figure S7. Correlation of an average of the microRNAs in the MIR99AHG cluster (mir-99a, let-7c and mir-125b-2) and the LINC00478 (MIR99AHG) from the mRNA expression cohort. The values are mean centered to ease the comparison. The slope is 0.4 indicating a better dynamic range for the detection of the microRNAs. Figure S8. A focused analysis on the Luminal A samples with stratification on whether or not the patient has received radiotherapy. (DOCX 3368 kb)