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Unsupervised clustering of DNA methylation profile

PG Pengfei Gu
YZ Yu Zeng
WM Weike Ma
WZ Wei Zhang
YL Yu Liu
FG Fengli Guo
XR Xianhui Ruan
JC Jiadong Chi
XZ Xiangqian Zheng
MG Ming Gao
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Probes that were unmethylated in the 48 normal samples (mean β-value < 0.3) and that had a standard deviation (SD) of greater than 0.15 in the tumor samples were chosen for the clustering. In addition to β-values, we used M-values in this study (M-value = log2(β/1 β) because of the stronger signals for quantifying methylation levels (34). Unsupervised hierarchical clustering with Ward’s method and Euclidean distance measurement was used to cluster the 350 primary tumor samples based on methylation M-values, and the clustering dendrogram was cut at k = 2 to yield two clusters.

Copyright and License information:  ©2022 Gu, Zeng, Ma, Zhang, Liu, Guo, Ruan, Chi, Zheng and Gao
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