• analisi
• conformazione
• epigenetica
• genoma
• Hi-C
• mappe di contatto
• tool
• tridimensionale

The biological information of the organisms is stored in the DNA, which folds up into elaborate physical structures inside the cell nucleus. The packing of the genetic material is not only useful to allow spatial compactness, but it assumes also a functional relevance. In such a way, the understanding that nuclear organization plays an important role in the epigenetic regulation poses considerable challenges.
During the past fifteen years, several techniques have been developed to explore the architecture of chromatin within the nucleus, such as Chromosome Conformation Capture (3C) and derived 3C protocols (4C, 5C) or Fluorescence In-Situ Hybridization (FISH). However, a genome-wide analysis was only possible after 2009, when the Hi-C protocol was introduced, which first allowed for a comprehensive mapping of genome interactions. In order to process Hi-C data, several software are needed to perform each step of the analysis, from the preprocessing to the visualization of the data. Moreover, a normalization procedure is required to remove biases, introduced by the experimental protocol itself or related to genome features.
To address these needs we developed HiCtool, a standardized bioinformatic pipeline that handles efficiently the Hi-C analysis, from the preprocessing and the normalization of the data to the visualization of heatmaps. HiCtool contains the first pipeline for the data preprocessing and also a section for the topological domains analysis, to allow further investigation about genomes conformations.
By using HiCtool, we successfully run several Hi-C datasets of different cell lines and conditions of human and mouse, with the aim of creating the biggest library of standardized processed data ever. We collected all these datasets on GITAR (Genome Interaction Tools and Resources), a framework we built to work on and manage genomic interaction data. GITAR contains either a standardized library to process Hi-C data (HiCtool) and the collection of datasets we processed. In such a way, we provide users a powerful and easy tool, both for analysis and epigenetic comparative studies on different species or conditions.