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Chicdiff: a computational pipeline for detecting differential chromosomal interactions in Capture Hi-C data.

Jonathan Cairns1,2, William R Orchard1,3,4,5, Valeriya Malysheva1,3,4

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Chicdiff, a new R package, robustly detects differential chromosomal interactions from Capture Hi-C data. This tool identifies cell type-specific interactions, linking them to gene expression changes.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Capture Hi-C is a key method for identifying chromosomal interactions involving specific DNA regions like gene promoters.
  • Analyzing differential interactions in Capture Hi-C data presents statistical challenges due to data properties.

Purpose of the Study:

  • To introduce Chicdiff, an R package designed for robust detection of differential interactions in Capture Hi-C data.
  • To provide specialized normalization and multiple testing methods tailored for Capture Hi-C data.

Main Methods:

  • Chicdiff utilizes an advanced differential testing approach for count data.
  • The package incorporates bespoke normalization and multiple testing procedures optimized for Capture Hi-C data characteristics.
  • Validation was performed on published Promoter Capture Hi-C datasets from human Monocytes and CD4+ T cells.

Main Results:

  • Chicdiff successfully identified numerous cell type-specific chromosomal interactions.
  • A positive correlation was confirmed between promoter interactions and gene expression levels.
  • The package demonstrates robust performance in detecting differential interactions.

Conclusions:

  • Chicdiff offers a reliable solution for analyzing differential interactions in Capture Hi-C experiments.
  • The findings highlight the importance of cell type-specific interactions in regulating gene expression.
  • The R package is publicly available for broader scientific use.