Motivation: Hi-C experiments have been widely adopted to study chromatin spatial organization, which plays an important role in genome function. Well-established Hi-C readouts include A/B compartments, topologically associating domains (TADs) and chromatin loops. We have recently proposed another readout: frequently interacting regions (FIREs) and discovered them to be informative about tissue-specific gene expression. However, computational tools for detecting FIREs from Hi-C data are still lacking. Results: In this work, we have developed FIREcaller, a stand-alone, user-friendly R package for detecting FIREs from Hi-C data. FIREcaller takes raw Hi-C contact matrix as input, performs within-sample and cross-sample normalization via HiCNormCis and quantile normalization respectively, and outputs continuous FIRE scores, dichotomous FIREs and super-FIREs. Availability and implementation: The FIREcaller package is implemented in R, freely available at https://yunliweb.its.unc.edu/FIREcaller.
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- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
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