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High depth genome wide chromatin contact matrix

dataset
posted on 06.10.2022, 20:59 authored by Ruchi LohiaRuchi Lohia, Nathan Fox, Jesse Gillis

These high-depth meta-Hi-C chromatin contact matrices are surprisingly powerful in capturing long-range functional relationships of chromatin interactions, which are now able to predict coexpression, eQTLs, and cross-species relationships. 

For building the meta-Hi-C matrix, we uniformly processed 3619, 6732, and 487 Hi-C runs for Human, Mouse, and Fly respectively. The runs were obtained after querying Sequence Read Archive with field limitations of given species and Hi-C as experiment strategy.  A genome-wide chromatin contact matrix was created for each run after mapping the reads to the same reference genome for each species. Reads were aligned to the hg38, mm10, and dm6 genomes in Human, Mouse and Fly respectively. All chromatin contact matrices for a species were aggregated to create the meta-Hi-C matrix. 

The genome-wide Hi-C matrices were divided into cis (intrachromsomal) and trans (interchromosomal). In cis, each chromosome is stored in a seperate matrix. In trans,  the matrix is genome-wide but with no cis contacts (cis contacts are always 0 in this case). Here the cis contact matrices are available at 10KB and 1KB resolution for all three species. The trans contact matrices are available at 10KB resolution for all three species and additionally at 1KB resolution for Fly. The matrices are stored as *.h5 in HiCMatrix format (https://github.com/deeptools/HiCMatrix). HiCExplorer (https://hicexplorer.readthedocs.io/en/latest/) can be used to process these files or to convert them to other formats if desired. 

Meta-Hi-C matrices at several other resolutions are available for download via online tool at https://gillisweb.cshl.edu/HiC/ or direct download at https://labshare.cshl.edu/shares/gillislab/resource/HiC/

Funding

Revealing the transcriptomic basis of neuronal identity through functional meta-analysis

National Institute of Mental Health

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Heuristics to evaluate biomedical and genomic knowledge bases for validity

United States National Library of Medicine

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Graphical Processing Units and a Large-Memory Compute Node for Applications in Genomics, Neuroscience, and Structural Biology

Office of the Director

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History

Research Institution(s)

Cold Spring Harbor Laboratory, University of Toronto

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