Retrieving Chromatin Patterns from Deep Sequencing Data Using Correlation Functions.
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ABSTRACT: Robust comparison of deep-sequencing data sets is often hampered by differences in their pattern structure or signal-to-noise ratio. Here, we established multi-scale correlation evaluation (MCORE), a method to dissect and compare the genome-wide topology of chromatin features. We applied MCORE to Hi-C, ChIA-PET, ChIP-seq, RNA-seq and Bisulfite-seq data from mouse embryonic stem cells and neural cells to track the extension, transformation and spatial repositioning of chromatin domains during differentiation.
ORGANISM(S): Mus musculus
PROVIDER: GSE61874 | GEO | 2016/12/31
SECONDARY ACCESSION(S): PRJNA262580
REPOSITORIES: GEO
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