Additional file 1 of cfNOMe — A single assay for comprehensive epigenetic analyses of cell-free DNA
Creators: name: Erger, Florian
name: Nörling, Deborah
name: Borchert, Domenica
name: Leenen, Esther
name: Habbig, Sandra
name: Wiesener, Michael S.
name: Bartram, Malte P.
name: Wenzel, Andrea
name: Becker, Christian
name: Toliat, Mohammad R.
name: Nürnberg, Peter
name: Beck, Bodo B.
name: Altmüller, Janine
Publisher: name: figshare
Year: 2020
Subjects: subject: Medicine
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Pharmacology
subject: Biotechnology
subject: Immunology
subject: FOS: Clinical medicine
subject: FOS: Clinical medicine
subject: 69999 Biological Sciences not elsewhere classified
subject: Cancer
subject: Hematology

description: Additional file 1: Figure S1. Basic principle of enzymatic cytosine conversion. Figure S2. Coverage by GC content of sequenced DNA. Figure S3. Comparison of mapping efficiency by method and input material. Figure S4. Donor SNP allele fraction in graft, patient blood and patient urine for P27 and P29. Figure S5. Methylation bias by read position. Figure S6. Global methylation levels in replicates for K16, K17, K18, P25, P27 and P29. Figure S7. Global methylation levels in K19, K20, K21 (Bisulfite and cfNOMe) and P30, P31 and P32. Figure S8. CpG and non-CpG methylation levels on chromosome 2. Figure S9. Clustermap of the methylation profiles of 25 reference tissues. Figure S10. Correlation between pyrosequencing and NGS methylation calls in enzymatic conversion. Figure S11. Cohort and experimental overview. Figure S12. CpG positions covered ≥1x in cfNOMe vs. Bisulfite sequencing. Figure S13. Coverage depth over CpG positions in cfNOMe vs. Bisulfite sequencing. Figure S14. Normalized WPS120 around the transcription start site (TSS) of expressed vs. non-expressed genes in whole blood. Figure S15. Correlation between the nucleosome positioning signal (NPS) and the level of gene expression, 200-500 bp cfDNA fragments. Figure S16. Downsampling series of nucleosome positioning signal as a function of dataset size. Figure S17. Blood-derived cfDNA fragment length histograms. Figure S18. Urine-derived cfDNA fragment length histograms. Figure S19. Violin plot of the interpeak distances in the WPS signal around high- and low-expression genes. Figure S20. Methylation profiles for all samples at 7890 informative differentially methylated CpGs. Figure S21. Methylation deconvolution results for blood-derived cfDNA samples. Figure S22. Methylation deconvolution results for urine-derived cfDNA samples. Figure S23. Deconvolution-calculated renal cfDNA fractions in patients vs. controls. Figure S24. Deconvolution-calculated cfDNA fractions with liver and pancreas tissue-of-origin in all samples. Figure S25. Pair-wise comparison of deconvolution results in replicates of the same sample. Table S1. Library preparation steps and DNA amounts in urine samples. Table S2. Library preparation steps and DNA amounts in blood samples, discovery cohort. Table S3. Library preparation steps and DNA amounts in blood samples, replication cohort. Table S4. Reaction composition using PyroMark PCR Master Mix. Table S5. PCR protocol for PyroMark PCR reaction. Table S6. Primer sequences and reaction conditions for loci of interest. Table S7. Sequencing and associated clinical data for each sample in this study, discovery cohort. Table S8. Sequencing and associated clinical data for each sample in this study, replication cohort.