Rich Chromatin Structure Prediction from Hi-C Data
نویسندگان
چکیده
منابع مشابه
An integrated model for detecting significant chromatin interactions from high-resolution Hi-C data
Here we present HiC-DC, a principled method to estimate the statistical significance (P values) of chromatin interactions from Hi-C experiments. HiC-DC uses hurdle negative binomial regression account for systematic sources of variation in Hi-C read counts-for example, distance-dependent random polymer ligation and GC content and mappability bias-and model zero inflation and overdispersion. App...
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Most genome browsers display DNA linearly, using single-dimensional depictions that are useful to examine certain epigenetic mechanisms such as DNA methylation. However, these representations are insufficient to visualize intrachromosomal interactions and relationships between distal genome features. Relationships between DNA regions may be difficult to decipher or missed entirely if those regi...
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Chromosome conformation capture (3C) techniques have revealed many fascinating insights into the spatial organization of genomes. 3C methods typically provide information about chromosomal contacts in a large population of cells, which makes it difficult to draw conclusions about the three-dimensional organization of genomes in individual cells. Recently it became possible to study single cells...
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We have analyzed publicly available K562 Hi-C data, which enable genome-wide unbiased capturing of chromatin interactions, using a Mixture Poisson Regression Model and a power-law decay background to define a highly specific set of interacting genomic regions. We integrated multiple ENCODE Consortium resources with the Hi-C data, using DNase-seq data and ChIP-seq data for 45 transcription facto...
متن کاملminiMDS: 3D structural inference from high-resolution Hi-C data
Motivation Recent experiments have provided Hi-C data at resolution as high as 1 kbp. However, 3D structural inference from high-resolution Hi-C datasets is often computationally unfeasible using existing methods. Results We have developed miniMDS, an approximation of multidimensional scaling (MDS) that partitions a Hi-C dataset, performs high-resolution MDS separately on each partition, and ...
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ژورنال
عنوان ژورنال: IEEE/ACM Transactions on Computational Biology and Bioinformatics
سال: 2019
ISSN: 1545-5963,1557-9964,2374-0043
DOI: 10.1109/tcbb.2018.2851200