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Supplementary Tables S1-S22 from Noninvasive Multicancer Detection Using DNA Hypomethylation of LINE-1 Retrotransposons

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Figshare2025-04-01 更新2026-04-28 收录
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Table S1. Targeted bisulfite sequencing primers Table S2. Target copies and CpG sites relative to the number of sequencing reads Table S3. Statistical results of global methylation differences between healthy samples and cancer subgroups using Mann–Whitney U test Table S4. List of plasma samples. Sample IDs were not known to anyone outside the research group Table S5. Statistical results of proportion differences between healthy samples and cancer subgroups for the 372 haplotypes using Mann–Whitney U test Table S6. List of paired plasma and tissues samples and their spearman correlation for various features Table S7. Breast cancer subtype composition of M0 and M+ subgroups in C1 and C2 Table S8. Mutation screening of ovarian cancer samples from the discovery cohort Table S9. Statistical results of proportion differences between healthy samples from C1 and C2 for 14 haplotypes selected using Mann–Whitney U test Table S10. Statistical results of global methylation differences between healthy samples and cancer subgroups from C1 and C2 using Mann–Whitney U test Table S11. Statistical results of proportion differences between healthy samples and cancer subgroups from C1 and C2 for 14 haplotypes selected using Mann–Whitney U test Table S12. Statistical results of global methylation differences between original data and age-adjusted data using Mann–Whitney U test Table S13. Statistical results of global methylation differences between cancer stages using Mann–Whitney U test Table S14. Statistical results of global methylation differences between primary and metastatic tissues using Mann–Whitney U test Table S15. Statistical results of Genome-wide z-score differences between healthy samples and cancer subgroups using Mann–Whitney U test Tables S16-S22. Cancer prediction and sample labelling with the 2-step classification integrating CNA analysis - healthy vs each type of model
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