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HiCdat
Provides a simple graphical user interface for data pre-processing and a collection of higher-level data analysis tools implemented in R. Data pre-processing also supports a wide range of additional data types required for in-depth analysis of the Hi-C data (e.g. RNA-Seq, ChIP-Seq, and BS-Seq). Importantly, HiCdat is focused on the analysis of larger structural features of chromosomes, their correlation to genomic and epigenomic features, and on comparative studies. It uses simple input and output formats and can therefore easily be integrated into existing workflows or combined with alternative tools.
HubPredictor
A computational model integrating Hi-C and histone mark ChIP-seq data to predict two important features of chromatin organization: chromatin interaction hubs and topologically associated domain (TAD) boundaries. HubPredictor accurately and robustly predicts these features across datasets and cell types. Cell-type specific histone mark information is required for prediction of chromatin interaction hubs but not for TAD boundaries. HubPredictor provides a useful guide for the exploration of chromatin organization.
3DGenome_FruitFly
Integrates experimental data obtained from different technologies to map the 3D structures of entire genomes. 3DGenome_FruitFly generates a large number of genome structures whose chromatin contacts are statistically consistent with those from the Hi-C data. It can be used for genomes of any organism, including mammalian genomes. The tool permits detailed analysis of the genome’s structural features, at high resolution and fully consistent with all experimental findings.
InPhaDel / Integrative Phasing of Deletions
A technique to phase deletions to SNVs using only WGS and HiC sequencing from a single human donor. Phasing SNVs and deletions is similar to the haplotype assembly problem. InPhaDel addresses the question of determining if heterozygous deletions act in cis or trans with other heterozygous variants. We formulate the task as a multi-class classification problem where deletions can be phased to either chromosome (pA or pB), homozygous or unsupported by the read data. We used Nearest Neighbors, SVM and Random Forest learning methods to solve this problem.
HiCfeat / Multiple Logistic Regression for 3D Chromatin Domain Border Analysis
Assess the influences of genomic features such as DNA-binding proteins and functional elements on topological domain borders. HiCfeat is an R package offering a multiple logistic regression that can be easily accommodate interactions between genomic features to assess the impact of co-occurrences on domain borders. This model outperforms enrichment test and nonparametric models in the identification of known and suspected architectural proteins.
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