HiTC

HiTC analyzes high-throughput 'C' data (3C-based datasets) in R/Bioconductor to import, transform, normalize, annotate, and visualize chromatin interaction maps for interpretation of genomic interactions.

Key Features:

• R/Bioconductor implementation: Provides an R package within Bioconductor enabling interoperability with Bioconductor data structures and tools.
• Data import/export: Functions to import and export chromatin interaction and 3C-based interaction data.
• Transformation: Tools to transform interaction matrices and contact data for analysis and visualization.
• Normalization: Normalization methods that adjust interaction data for technical variation to improve comparability.
• Annotation: Routines to link interaction maps with genomic and biological annotations.
• Quality control: Methods for quality assessment of 3C-based datasets to evaluate data integrity and consistency.
• Visualization: Visualization tools to generate detailed chromatin interaction maps for exploration and interpretation.

Scientific Applications:

• Chromatin interaction analysis: Characterization of chromatin contact patterns and interaction maps from 3C-based datasets.
• Data preprocessing: Preprocessing and normalization of interaction data to correct technical biases before downstream analyses.
• Quality assessment: Assessment of dataset integrity and consistency to identify technical issues prior to analysis.
• Functional interpretation: Annotation and visualization of interaction maps to link contacts with genomic annotations and generate hypotheses about genomic organization and function.

Methodology:

Explicit methods include importing and exporting interaction data, data transformation, normalization to adjust for technical variation, quality-control routines, annotation of interaction maps, and visualization within the Bioconductor framework.