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Additional file 2: Fig. 1. The algorithm with high sensitivity for identifying recurrence of breast cancer

Additional file 3: Fig. 2.The algorithm with high positive predictive value for identifying recurrence of breast cancer

Additional file 4: Fig. 3. The algorithm with high overall accuracy for identifying recurrence of breast cancer

Additional file 1: Table 1. The codes used for defining the study variables

Additional file 1. Themes and exemplar quotes. Table of study data including themes and corresponding participant quotes

Additional file 4: Figure S3. Contributions of 30 COSMIC mutational signatures. Contributions of 30 COSMIC mutational signatures to the mutational spectra of (A) young-onset breast tumours (diagnosed at ≤40 years of age, n = 89) and (B) older-onset breast tumours (diagnosed at > 40 years of age, n = 949). Sorted by signature contribution.

Additional file 1: Figure S1. Contribution of 30 COSMIC mutational signatures by PAM50 subtype. Contributions of 30 COSMIC mutational signatures to the mutational spectra of (A) young-onset breast tumours (diagnosed at ≤40 years of age, n = 77) and (B) older-onset breast tumours (diagnosed at > 40 years of age, n = 771). Sorted by PAM50 subtype. Cases with unknown subtype were excluded. HER2+: human epidermal growth factor receptor 2 over-expressing; PAM50: prediction analysis of microarrays 50 gene set.

Additional file 8: Figure S7. Contributions of five mutational signatures. Contributions of five signatures identified using R package “SomaticSignatures” to the mutational spectra of (A) young-onset breast tumours (diagnosed at ≤40 years of age, n = 89) and (B) older-onset breast tumours (diagnosed at > 40 years of age, n = 949).

Additional file 2: Figure S2. Proportion of mutation types. Proportions of the six mutation types among SNVs observed in (A) young-onset breast tumours (diagnosed at ≤40 years of age, n = 89) and (B) older-onset breast tumours (diagnosed at > 40 years of age, n = 949), sorted by percent of C > T mutations. SNV: Single Nucleotide Variant.

Additional file 7: Figure S6. Contributions of sixteen mutational signatures. Contribution of sixteen signatures identified using R package “SomaticSignatures” to the mutational spectra of (A) young-onset breast tumours (n = 89) and (B) older-onset breast tumours (n = 949).

Additional file 3: Table S1. Signature contributions across age of onset groups. Summary of contributions of COSMIC signatures to mutational spectra, including the mean contribution of each signature in each age of onset group, and the prevalence in each age of onset group.