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.
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.
Allows to analyze, compare, and visualize next generation sequencing (NGS) data. CLC Genomics Workbench offers a complete and customizable solution for genomics, transcriptomics, epigenomics, and metagenomics. The software enables to generate custom workflows, which can combine quality control steps, adapter trimming, read mapping, variant detection, and multiple filtering and annotation steps into a pipeline.
A high-throughput identification pipeline for promoter interacting enhancer element to streamline the workflow from mapping raw Hi-C reads, identifying DNA-DNA interacting fragments with high confidence and quality control, detecting histone modifications and DNase hypersensitive enrichments in putative enhancer elements, to ultimately extracting possible intra- and inter-chromosomal enhancer-target gene relationships.
A hidden Markov random field based Bayesian peak caller to identify long range chromatin interactions from Hi-C data. Comparing to the existing anchor-fragment peak caller, HMRFBayesHiC is the first two-dimensional peak caller, which takes observed and expected Hi-C contact matrix as the input files. HMRFBayesHiC explicitly models the spatial dependency of chromatin interaction among adjacent neighborhood regions, resulting in superior reproducibility and enhanced statistical power.
A hidden Markov random field (HMRF)-based peak caller to detect long-range chromosomal interactions from Hi-C data. In real Hi-C data analysis, FastHiC runs around ten times faster than our previous Bayesian version peak caller HMRFBayes. The substantial speed-up comes from a novel implementation of simulated field approximation, which approximates the joint distribution of the hidden peak status by a set of independent random variables, leading to more tractable computation.
Offers functions for the analysis of chromatin interactions using MC_DIST model (one sample problem), Two-Step model and One-Step model. MDM provides: (i) a function MCDIST to detect ture chromatin interactions using a dataset obtained from a chromatin looping experiment, (ii) a function MDTS to peoform the second step of the Two-Step model for detecting chromatin interactions with different intensities in two samples, and (iii) a function MDOS to peoform the One-Step model for detecting chromatin interactions with different intensities in two samples.
Provides users with a statistical pipeline for analysing chromosomal interactions data (Hi-C data). chromoR combines wavelet methods and a Bayesian approach for correction (bias and noise) and comparison (detecting significant changes between Hi-C maps) of Hi-C contact maps. In addition, it also support detection of change points in 1D Hi-C contact profiles. The chromoR package provides researchers with a means to analyse chromosomal interaction data using statistical bioinformatics, offering a new and comprehensive solution to this task.
Uses for interacting with the PGL file standard for paired-genomic loci. Pgltools is a cross platform, pypy compatible python package available both as an easy-to-use UNIX package, and as a python module, for integration into pipelines of paired-genomic-loci analyses. This software performs genomic arithmetic on PGL files such as comparing, merging, and intersecting two sets of paired-genomic-loci, as well as integrates BED files with PGL files.
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.
0 - 0 of 0
1 - 5 of 5
0 - 0 of 0