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Loop detection using Hi-C data with HiCExplorer.

Joachim WolffRolf BackofenBjoern Andreas Gruening
Published in: GigaScience (2022)
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.
Keyphrases
  • electronic health record
  • big data
  • machine learning
  • deep learning
  • mass spectrometry
  • artificial intelligence