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2. Data from Genetic and Environmental Causes of Variation in an Automated Breast Cancer Risk Factor Based on Mammographic Textures

3. Supplementary Methods S1 from Genetic and Environmental Causes of Variation in an Automated Breast Cancer Risk Factor Based on Mammographic Textures

4. Supplementary Figure S1 from Genetic and Environmental Causes of Variation in an Automated Breast Cancer Risk Factor Based on Mammographic Textures

5. Supplementary Table S1 from Genetic and Environmental Causes of Variation in an Automated Breast Cancer Risk Factor Based on Mammographic Textures

6. Table S2. from Adherence to 2018 WCRF/AICR Cancer Prevention Recommendations and Risk of Cancer: The Melbourne Collaborative Cohort Study

7. Figure S1. from Adherence to 2018 WCRF/AICR Cancer Prevention Recommendations and Risk of Cancer: The Melbourne Collaborative Cohort Study

8. Data from Adherence to 2018 WCRF/AICR Cancer Prevention Recommendations and Risk of Cancer: The Melbourne Collaborative Cohort Study

9. Genetic and environmental causes of variation in an automated breast cancer risk factor based on mammographic textures

10. Adherence to 2018 WCRF/AICR cancer prevention recommendations and risk of cancer: the Melbourne Collaborative Cohort Study

11. Figure S3 from Using DEPendency of Association on the Number of Top Hits (DEPTH) as a Complementary Tool to Identify Novel Colorectal Cancer Susceptibility Loci

12. Table S8 from Using DEPendency of Association on the Number of Top Hits (DEPTH) as a Complementary Tool to Identify Novel Colorectal Cancer Susceptibility Loci

13. Data from Using DEPendency of Association on the Number of Top Hits (DEPTH) as a Complementary Tool to Identify Novel Colorectal Cancer Susceptibility Loci

14. Using DEPendency of Association on the Number of Top Hits (DEPTH) as a Complementary Tool to Identify Novel Colorectal Cancer Susceptibility Loci

19. Supplementary Tables 1-3 from A Genome-Wide Gene-Based Gene–Environment Interaction Study of Breast Cancer in More than 90,000 Women

20. Supplementary Figure 1 from A Genome-Wide Gene-Based Gene–Environment Interaction Study of Breast Cancer in More than 90,000 Women

21. Supplementary Information from A Genome-Wide Gene-Based Gene–Environment Interaction Study of Breast Cancer in More than 90,000 Women

22. Data from A Genome-Wide Gene-Based Gene–Environment Interaction Study of Breast Cancer in More than 90,000 Women

24. Supplementary Table 3 from Rare Mutations in RINT1 Predispose Carriers to Breast and Lynch Syndrome–Spectrum Cancers

25. Data from Breast Cancer Chemoprevention: Use and Views of Australian Women and Their Clinicians

26. Supplementary Data 1 from Breast Cancer Chemoprevention: Use and Views of Australian Women and Their Clinicians

27. Supplementary Methods, Figures S1 - S3 from Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types

28. Supplementary Tables S1 - S10 from Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types

29. Data from Weight is More Informative than Body Mass Index for Predicting Postmenopausal Breast Cancer Risk: Prospective Family Study Cohort (ProF-SC)

30. Supplementary Figure 1 from Rare Mutations in RINT1 Predispose Carriers to Breast and Lynch Syndrome–Spectrum Cancers

32. Supplementary Data from Weight is More Informative than Body Mass Index for Predicting Postmenopausal Breast Cancer Risk: Prospective Family Study Cohort (ProF-SC)

34. Supplementary Table 2 from Rare Mutations in RINT1 Predispose Carriers to Breast and Lynch Syndrome–Spectrum Cancers

35. Supplementary Table 1 from Rare Mutations in RINT1 Predispose Carriers to Breast and Lynch Syndrome–Spectrum Cancers

36. Supplementary Data 4 from Breast Cancer Chemoprevention: Use and Views of Australian Women and Their Clinicians

37. Supplementary Acknowledgments from Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types

38. Supplementary Data 2 from Breast Cancer Chemoprevention: Use and Views of Australian Women and Their Clinicians

39. Data from Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types

41. Supplementary Grant Support from Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types

42. Supplementary Data 3 from Breast Cancer Chemoprevention: Use and Views of Australian Women and Their Clinicians

43. Data from Rare Mutations in RINT1 Predispose Carriers to Breast and Lynch Syndrome–Spectrum Cancers

44. Supplementary Table 1 from Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations

45. Appendix from Use of a Novel Nonparametric Version of DEPTH to Identify Genomic Regions Associated with Prostate Cancer Risk

46. Data from Accuracy of Self-Reported Nevus and Pigmentation Phenotype Compared with Clinical Assessment in a Population-Based Study of Young Australian Adults

47. Data from Risk Analysis of Prostate Cancer in PRACTICAL, a Multinational Consortium, Using 25 Known Prostate Cancer Susceptibility Loci

48. Data from Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations

49. Supplementary Methods, Tables 1 - 6 from A Genome-wide Association Study of Early-Onset Breast Cancer Identifies PFKM as a Novel Breast Cancer Gene and Supports a Common Genetic Spectrum for Breast Cancer at Any Age

50. Supplementary Tables and References from BRCA2 Hypomorphic Missense Variants Confer Moderate Risks of Breast Cancer

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