HPTAD: A computational method to identify topologically associating domains from HiChIP and PLAC-seq datasets
Jonathan Rosen1, Lindsay Lee2, Armen Abnousi2
1Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
Abstract:
High-throughput chromatin conformation capture technologies, such as Hi-C and Micro-C, have enabled genome-wide view of chromatin spatial organization. Most recently, Hi-C-derived enrichment-based technologies, including HiChIP and PLAC-seq, offer attractive alternatives due to their high signal-to-noise ratio and low cost. While a series of computational tools have been developed for Hi-C data, methods tailored for HiChIP and PLAC-seq data are still under development. Here we present HPTAD, a computational method to identify topologically associating domains (TADs) from HiChIP and PLAC-seq data. We performed comprehensive benchmark analysis to demonstrate its superior performance over existing TAD callers designed for Hi-C data. HPTAD is freely available at https://github.com/yunliUNC/HPTAD.
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