Related Experiment Video
Updated: Sep 6, 2025
Targeted DNA Methylation Analysis by Next-generation Sequencing
Published on: February 24, 2015
MeConcord: a new metric to quantitatively characterize DNA methylation heterogeneity across reads and CpG sites
1Ministry of Education Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Bioinformatics Division, Beijing National Research Center for Information Science and Technology, Department of Automation, Tsinghua University, Beijing 100084, China.
Motivation:
Intermediately methylated regions occupy a significant fraction of the human genome and are closely associated with epigenetic regulations or cell-type deconvolution of bulk data. However, these regions show distinct methylation patterns, corresponding to different biological mechanisms. Although there have been some metrics developed for investigating these regions, the high noise sensitivity limits the utility for distinguishing distinct methylation patterns.
Results:
We proposed a method named MeConcord to measure local methylation concordance across reads and CpG sites, respectively. MeConcord showed the most stable performance in distinguishing distinct methylation patterns ('identical', 'uniform' and 'disordered') compared with other metrics. Applying MeConcord to the whole genome data across 25 cell lines or primary cells or tissues, we found that distinct methylation patterns were associated with different genomic characteristics, such as CTCF binding or imprinted genes. Further, we showed the differences of CpG island hypermethylation patterns between senescence and tumorigenesis by using MeConcord. MeConcord is a powerful method to study local read-level methylation patterns for both the whole genome and specific regions of interest.
Availability And Implementation:
MeConcord is available at https://github.com/WangLabTHU/MeConcord.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
