HiCapTools

HiCapTools performs targeted probe design and contact analysis for chromosome conformation capture methods (T2C, chi-C, and HiCap) to detect and statistically evaluate physical contacts between genomic regions for studies of 3D genome architecture and gene regulation.


Key Features:

  • Probe Design: Designs two sequence capture probes per genomic feature while avoiding repeat elements and non-unique regions to specifically capture targeted restriction fragments.
  • Data Analysis Suite: Processes sequencing alignment files to detect and report genomic proximities at the restriction fragment level and performs isoform-aware analysis for gene features.
  • Statistical Evaluation: Assesses the significance of detected contact frequencies using an empirically derived background distribution.

Scientific Applications:

  • Genome architecture and gene regulation: Identifies physical contacts between regulatory elements and genes to study how 3D folding influences gene regulation and chromatin dynamics.
  • Chromatin dynamics and cellular function: Maps targeted physical interactions to investigate relationships between spatial genome organization and cellular processes.
  • GWAS variant-to-gene mapping: Supports linking disease-associated variants from GWAS to candidate target genes via detected physical contacts.

Methodology:

Computationally designs two capture probes per feature avoiding repeats and non-unique regions, processes sequencing alignment files to map contacts at the restriction fragment level with isoform-aware handling of gene features, and evaluates contact significance using an empirically derived background distribution.

Topics

Details

Tool Type:
workflow
Operating Systems:
Linux
Programming Languages:
C++
Added:
6/20/2018
Last Updated:
11/25/2024

Operations

Publications

Anil A, Spalinskas R, Åkerborg Ö, Sahlén P. HiCapTools: a software suite for probe design and proximity detection for targeted chromosome conformation capture applications. Bioinformatics. 2017;34(4):675-677. doi:10.1093/bioinformatics/btx625. PMID:29444232. PMCID:PMC6368139.

PMID: 29444232
PMCID: PMC6368139
Funding: - Swedish Research Council: 78081

Documentation