Statistical Estimation of Mutual Information for Mixed Model

Bulinski, Alexander; Kozhevin, Alexey

doi:10.1007/s11009-020-09802-0

Cited by 5 publications

(1 citation statement)

References 18 publications

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“…In this study, we utilized mutual information [20] , [21] , [22] as an indication for general correlation (relevance) between a pair of genomic features, and mathematically integrated it with the number of colocalizations between the features to define a score for maximal colocalization minimal correlation (MACMIC). The MACMIC score allows us to quantitatively prioritize the feature combinations that have large number of colocalizations but low correlation.…”

Section: Introductionmentioning

confidence: 99%

MACMIC Reveals a Dual Role of CTCF in Epigenetic Regulation of Cell Identity Genes

Wang

Xia

Zhou³

et al. 2021

Genomics, Proteomics &Amp; Bioinformatics

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Numerous studies of relationship between epigenomic features have focused on their strong correlation across the genome, likely because such relationship can be easily identified by many established methods for correlation analysis. However, two features with little correlation may still colocalize at many genomic sites to implement important functions. There is no bioinformatic tool for researchers to specifically identify such feature pairs. Here, we develop a method to identify feature pairs in which two features have maximal colocalization minimal correlation (MACMIC) across the genome. By MACMIC analysis of 3306 feature pairs in 16 human cell types, we reveal a dual role of CCCTC-binding factor (CTCF) in epigenetic regulation of cell identity genes. Although super-enhancers are associated with activation of target genes, only a subset of super-enhancers colocalized with CTCF regulate cell identity genes. At super-enhancers colocalized with CTCF, CTCF is required for the active marker H3K27ac in cell types requiring the activation, and also required for the repressive marker H3K27me3 in other cell types requiring repression. Our work demonstrates the biological utility of the MACMIC analysis and reveals a key role for CTCF in epigenetic regulation of cell identity. The code for MACMIC is available at https://github.com/bxia888/MACMIC .

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Section: Introductionmentioning

confidence: 99%