Extended Data Fig. 7: Development and validation of epitype assignment and epiCMIT in RRBS data.

a. Consensus clustering matrices for K = 3 groups for paired-end (n = 136; 153 CpGs in consensus matrix) and single-end (n = 388; 32 CpGs) RRBS data. (d). b. Empirical cumulative distribution functions (CDFs) for consensus matrices with K = 2 to K = 7. c. Relative change under the CDF for K = 2 to K = 7. d. Heatmaps of the CpGs used for consensus clustering in (a). Each sample (columns) is annotated by tracks: epitype max probability, IGHV status (M-CLL, purple; U-CLL, orange), IGHV percent identity, and presence of IGLV3-21^R110 mutation (black). e. The development of the new epiCMIT methodology for RRBS data. The genome was segmented into Chromatin Hidden Markov Model (CHMM)²⁴ states using ChIP-seq data to get repressed chromatin regions, where differential DNA methylation analyses was performed in high coverage whole-genome bisulfite sequencing (WGBS) data between the cells with the lowest and highest accumulated cell divisions in the B cell lineage, namely the hematopoietic precursor cells (HPC) and bone-marrow plasma cells (bmPC). Only CPGs showing extensive differences were retained and constituted the epiCMIT-hyper CpGs or epiCMIT-hypo CpGs depending whether they gain or lose DNA methylation from <0.1 to ≥0.5 and from >0.9 to ≤0.5 from HPC to bmPC, respectively. EpiCMIT-hyper and epiCMIT-hypo scores were calculated according to the available epiCMIT-CpGs per sample, and the higher score in each sample was then selected. f. epiCMIT values on the same samples profiled twice with different platforms. Approach 1 - profiled with Illumina-450K (green); approach 2 - profiled with RRBS-PE (violet). In samples profiled with Illumina 450K, the original epiCMIT-CpGs were used⁵². In samples profiled with RRBS, epiCMIT was calculated with all available epiCMIT-CpGs for the new catalog (e, Methods). P-value by Pearson correlation test, two-sided; Error band − 95% confidence intervals of the Pearson correlation coefficient.