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- W4284990903 abstract "Chromatin loops are an essential factor in the structural organization of the genome; however, their detection in Hi-C interaction matrices is a challenging and compute-intensive task. The approach presented here, integrated into the HiCExplorer software, shows a chromatin loop detection algorithm that applies a strict candidate selection based on continuous negative binomial distributions and performs a Wilcoxon rank-sum test to detect enriched Hi-C interactions.HiCExplorer's loop detection has a high detection rate and accuracy. It is the fastest available CPU implementation and utilizes all threads offered by modern multicore platforms.HiCExplorer's method to detect loops by using a continuous negative binomial function combined with the donut approach from HiCCUPS leads to reliable and fast computation of loops. All the loop-calling algorithms investigated provide differing results, which intersect by $sim 50%$ at most. The tested in situ Hi-C data contain a large amount of noise; achieving better agreement between loop calling algorithms will require cleaner Hi-C data and therefore future improvements to the experimental methods that generate the data." @default.
- W4284990903 created "2022-07-11" @default.
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- W4284990903 date "2022-01-01" @default.
- W4284990903 modified "2023-10-18" @default.
- W4284990903 title "Loop detection using Hi-C data with HiCExplorer" @default.
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- W4284990903 doi "https://doi.org/10.1093/gigascience/giac061" @default.
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