
ABSTRACT Chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) is a method for the genome-wide de novo discovery of chromatin interactions. Existing computational methods typically fail to detect weak or dynamic interactions because they use a peak-calling step that ignores paired-end linkage information. We have developed a novel computational method called Chromatin Interaction Discovery (CID) to overcome this limitation with an unbiased clustering approach for interaction discovery. CID outperforms existing chromatin interaction detection methods with improved sensitivity, replicate consistency, and concordance with other chromatin interaction datasets. In addition, CID also outperforms other methods in discovering chromatin interactions from HiChIP data. We expect that the CID method will be valuable in characterizing 3D chromatin interactions and in understanding the functional consequences of disease-associated distal genetic variations.
Expressed Sequence Tags, Chromatin Immunoprecipitation, Computational Biology, Datasets as Topic, Sequence Analysis, DNA, Chromatin, DNA-Binding Proteins, Methods Online, Humans, Algorithms, Protein Binding
Expressed Sequence Tags, Chromatin Immunoprecipitation, Computational Biology, Datasets as Topic, Sequence Analysis, DNA, Chromatin, DNA-Binding Proteins, Methods Online, Humans, Algorithms, Protein Binding
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