FIREcaller: Detecting frequently interacting regions from Hi-C data
نویسندگان
چکیده
منابع مشابه
Exploring spatially adjacent TFBS-clustered regions with Hi-C data
Motivation Transcription factor binding sites (TFBSs) are clustered in the human genome, forming the TFBS-clustered regions that regulate gene transcription, which requires dynamic chromatin configurations between promoters and distal regulatory elements. Here, we propose a regulatory model called spatially adjacent TFBS-clustered regions (SATs), in which TFBS-clustered regions are connected by...
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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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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: Computational and Structural Biotechnology Journal
سال: 2021
ISSN: 2001-0370
DOI: 10.1016/j.csbj.2020.12.026