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HiCExplorer - set of programs to process, normalize, analyze and visualize Hi-C data, Python, .cool format, conversion utilities. https://hicexplorer.readthedocs.io/en/latest/, https://github.com/deeptools/HiCExplorer/
- Ramírez, Fidel, Vivek Bhardwaj, Laura Arrigoni, Kin Chung Lam, Björn A. Grüning, José Villaveces, Bianca Habermann, Asifa Akhtar, and Thomas Manke. “High-Resolution TADs Reveal DNA Sequences Underlying Genome Organization in Flies.” Nature Communications 9, no. 1 (December 2018)
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FAN-C - Python pipeline for Hi-C processing. Input - raw FASTQ (aligned using BWA or Bowtie2, artifact filtering) or pre-aligned BAMs. KR or ICE normalization. Analysis and Visualization (contact distance decay, A/B compartment detection, TAD/loop detection, Average TAD/loop profiles, saddle plots, triangular heatmaps, comparison of two heatmaps). Automatic or modular. Compatible with .cool and .hic formats. Tweet1, Tweet2. Table 1 - detailed comparison of 13 Hi-C processing tools
- Kruse, Kai, Clemens B. Hug, and Juan M. Vaquerizas. “FAN-C: A Feature-Rich Framework for the Analysis and Visualisation of Chromosome Conformation Capture Data.” Genome Biology 21, no. 1 (December 2020)
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GENOVA - an R package for the most common Hi-C analyses and visualization. Quality control - cis/trans ratio, checking for translocations; A/B compartments - single and differential compartment signal (H3K4me1 for compartment assignment); TADs - insulation score and directionality index; Genomic annotations - ChIP-seq signal, gene information; Distance decay, and differential analysis; Saddle plot; Aggregate region/peak/TAD/loop analysis, and differential analysis; Aggregated signal (tornado) plots; Intra-inter-TAD interaction differences; PE-SCAn (paired-end Spatial Chromatin Analysis) and C-SCAn enhancer-promoter aggregation. Data for statistical tests can be extracted from the discovery objects. Applied to Hi-C data from Hap1 cells, WT and deltaWAPL (published) and knockdown cohesin-SA1/SA2 conditions (HiC-pro, hg19, HiCCUPS). Input - HiC-pro, Juicer, .cool files. Storage - compressed sparse triangle format and the user-added metadata. All tools return the "discovery object". GitHub, Vignette
- Weide, Robin H. van der, Teun van den Brand, Judith H.I. Haarhuis, Hans Teunissen, Benjamin D. Rowland, and Elzo de Wit. “Hi-C Analyses with GENOVA: A Case Study with Cohesin Variants.” Preprint. Genomics, January 24, 2021.
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cooltools - tools to work with .cool files, Documentation
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HiGlass - visualization server for Google maps-style navigation of Hi-C maps. Overlay genes, epigenomic tracks. "Composable linked views" synchronizing exploration of multiple Hi-C datasets linked by location/zoom. GitHub, documentation, links and resources
- Kerpedjiev, Peter, Nezar Abdennur, Fritz Lekschas, Chuck McCallum, Kasper Dinkla, Hendrik Strobelt, Jacob M. Luber, et al. “HiGlass: Web-Based Visual Exploration and Analysis of Genome Interaction Maps.” Genome Biology, (December 2018).