Performs peak finding and downstream data analysis for next-generation sequencing analysis. HOMER affords several tools and methods to make use of ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and other types of functional genomics sequencing data sets. This software offers support to UCSC visualization, peaks annotation, quantification of transcripts and repeats or differential features, enrichment and expression.
A probabilistic model for Hi-C data and explore chromosomal architectures in human lymphoblasts using it. Hicpipe is a set of scripts and programs that correct Hi-C contact maps, given a list restriction enzyme sites and mapped paired reads.
Analyzes terabase-scale Hi-C datasets. Juicer allows users without a computational background to transform raw sequence data into normalized contact maps with one click. Juicer produces a hic file containing compressed contact matrices at many resolutions, facilitating visualization and analysis at multiple scales.
Maps, filters and analyzes Hi-C data. hiclib integrates a strategy to map sequencing reads with a data-driven method for iterative correction of biases, yielding genome-wide maps of relative contact probabilities. This library consists of three parts: mapping pipeline (mapping.py), fragment-level filtering pipeline (FragmentHiC.py), and a binned data analysis toolset (BinnedData.py).
A computational pipeline that integrates a strategy to map sequencing reads with a data-driven method for iterative correction of biases, yielding genome-wide maps of relative contact probabilities. Iterative correction leverages the unique pairwise and genome-wide structure of Hi-C data to decompose contact maps into a set of biases and a map of relative contact probabilities between any two genomic loci, achieving equal visibility across all genomic regions.
Facilitates the exploration of high-throughput 3C-based data. HiTC allows users to import and export ‘C’ data, to transform, normalize, annotate and visualize interaction maps. It proposes a powerful and extensible framework for visualizing and exploring high-throughput C data and is able to handle both 5C and Hi-C data and offers new functionalities such as standard import, data transformation and integrative visualization methods. The HiTC package is aimed at biologists interested in investigating their data and at biostatisticians involved in the development of new statistical methods which can be applied to C data.
Simplifies the Hi-C data pre-processing, contact matrix transformation, and topologically associating domain (TAD) calling into a few easy steps. HiCExplorer is a tool-suite that can be used with other pipelines and processing tools as we have built-in import/export functions covering commonly used Hi-C data formats. This method works with HiCBrowser, a browser and an underlying program to visualize Hi-C and other genomic tracks.
Designs to process Hi-C data, from raw fastq files (paired-end Illumina data) to the normalized contact maps. The pipeline is flexible, scalable and optimized. It can operate either on a single laptop or on a computational cluster using the PBS-Torque scheduler
Examines epigenomic and transcriptomic next generation sequencing (NGS) data. Octopus-toolkit can be used for antibody- or enzyme-mediated experiments and studies for the quantification of gene expression. It can accelerate the data mining of public epigenomic and transcriptomic NGS data for basic biomedical research. This tool provides a private and a public mode: one to process the user’s own data, and the other to analyze public NGS data by retrieving raw files from the GEO database.
Allows detection of collaborative transcription factor pairs. MMARGE consists of a suite of software tools to analyze ChIP-seq, ATAC-seq, DNase I Hypersensitivity or other next generation sequencing (NGS) assays where genotyping or DNA sequence data is available. For performing, this tool needs two types of data: (1) genetic variation, and (2) high-throughput sequencing data (ChIP-seq, ATAC-seq, DNaseI-seq).
Allows analysis and 3D modelling of 3C-based data. TADbit is a computational framework including: (i) read quality control and design of the mapping strategy; (ii) mapping of reads to the reference genome; (iii) interaction map filtering and normalization; (iv) interaction matrix analysis, including matrix comparison, Topologically Associating Domain (TAD) detection and TAD alignment; (v) 3D modelling of genomes and genomic domains; and (vi) 3D model analysis.
An approach to infer a consensus 3D structure of a genome from Hi-C data. The method incorporates a statistical model of the contact counts, assuming that the counts between two loci follow a Poisson distribution whose intensity decreases with the physical distances between the loci. The method can automatically adjust the transfer function relating the spatial distance to the Poisson intensity and infer a genome structure that best explains the observed data.
Allows a comprehensive and reproducible analysis of Hi-C sequencing data. HiC-bench performs complete Hi-C analysis starting with the alignment of reads (fastq files) and ending with the annotation of specific interactions, their visualization and enrichment analysis. Hi-C pipeline integrates Anchoring Topological Domain (TAD) calling HiC-bench using published methods and your own algorithm and performs calculation of boundary scores using your own methods and existing ones. Every pipeline step is followed by summary statistics (when applicable) and visualization of the results. This allows quality control and facilitates troubleshooting. Furthermore, HiC-bench allows parameter exploration and comparison of different methods in a combinatorial fashion. This feature facilitates the design and execution of complex benchmark studies that may involve combinations of multiple parameter/tool choices in each step.
A web server for analyzing spatial contact of chromosomes from the publicly available Hi-C data. ChromContact is designed to be simple and easy to use. By specifying a locus of interest, ChromContact calculates contact profiles and generates links to the UCSC Genome Browser, enabling users to visually examine the contact information with various annotations. ChromContact provides wide-range of molecular biologists with a user-friendly means to access high-resolution Hi-C data. One of the possible applications of ChromContact is investigating novel long-range promoter-enhancer interactions. This facilitates the functional interpretation of statistically significant markers identified by GWAS or ChIP-seq peaks that are located far from any annotated genes.
Detects the spatial proximity between pairs of genomic loci. GOTHiC is a binomial model that corrects the complex combination of known and unknown biases in Hi-C data by assuming that all biases are captured in the total number of reads mapping to the interacting loci. Significance levels and observed/expected ratios obtained from GOTHiC can be used as the basis for algorithms predicting the 3D structure of genome or those finding topologically associated domains.
Offers a statistical model dedicated to the mapping of physical contacts between different regions of DNA. Peaky provides an approach based on a Bayesian sparse variable selection that exploits peaks in a Capture hydrophobic-interaction chromatography Hi-C (CHi-C) signal. It can determine prey fragments with biological features that may be observed at sites of direct contact. The application is able to take into accounts of technical and biological noise.
Predicts interactions between pairs of regions across multiple cell lines. HiC-Reg is a random forest regression-based approach that integrates published Hi-C datasets with one-dimensional regulatory genomic datasets, such as chromatin marks or architectural and transcription factor proteins, to infer interaction counts between two genomic loci in a cell line-specific manner. The software can be used to predict contact counts in new cell lines, to examine long-range interactions for individual loci and for studying the organizational properties of chromosome conformation.
A bioinformatics pipeline for the automated analysis of data generated by high-throughput chromatin conformation capture (HiC). The analysis workflow comprises steps of data formatting, genome alignment, quality control and filtering, identification of genome-wide chromatin interactions, visualization and statistics. An interactive browser enables visual inspection of interaction data and results.
Offers a set of methods to perform high-resolution analyses of 3D genome organization using Hi-C data. HIFI is an application able to produce estimates of interaction frequencies (Ifs) at restriction fragments (RF) resolution. HIFI consists of three main part enabling IF evaluation, scripts for input data formatting and true-size IF matrix visualization able to generate both a normalized or non-normalized outputs.
Assists users in analyzing long-range chromatin interactions from proximity ligation assisted ChIP-seq (PLAC-seq) and HiChIP experiments. MAPS processes the data from such experiments and identifies long-range chromatin interactions. It utilizes the normalized chromatin contact frequencies to detect significant chromatin interactions anchored at genomic regions bound by the protein of interest.