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Unclassified software tools | Hi-C data analysis

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Utilizes chromatin contact maps to identify translocations in cancer cell lines. HiCtrans is a computational method scans fixed-size resolution inter-chromosomal contact maps of each chromosome pair for potential translocations using change-point statistics. This pipeline starts with performing binary segmentation independently on each row and column of an inter-chromosomal matrix. It then aggregates the change points identified from the perspective of each chromosome to determine rectangular boxes of contact enrichment with respect to the overall inter-chromosomal matrix.
Utilizes chromatin contact maps to identify copy number variations (CNVs) in cancer cell lines. HiCnv is a computational method that works on contact counts at the single restriction enzyme (RE) fragment level in order to leverage Hi-C data at its highest possible and native resolution. This method first computes 1D read coverage for each RE fragment, followed by normalization, smoothing and segmentation. Then, it processes for refinement of their breakpoint coordinates (segment ends) and assignment of their CNV labels.
GeSICA / Genome Segmentation from Intra Chromosomal Associations
Allows to explore genome organization. GeSICA calculates a simple logged ratio to efficiently segment the human genome into regions with two distinct states that correspond to rich and poor functional element states. It quantifies the degree of chromatin openness by using the principle that the assumption that random short-range DNA interactions would be easier to detect in open chromatin environments, and that the calculated interaction ratio could be regarded as an index.
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