Allows users to treat the imputation problem as a tensor completion task, and employs a parallelized algorithm based on the PARAFAC/ CANDECOMP method. PREDICTD assists users in modelling the epigenome based on the Encyclopedia of DNA Elements. Moreover, this tool can impute thousands of epigenomic maps in parallel using a 3D tensor factorization model.
Allows users to work on relationship between gene expression and chromatin features. Chromodel is a framework for relating chromatin features with gene expression. This tool is useful for researchers that wish to predict gene expression of protein coding genes, like microRNAs. It can work in several contexts, and especially on the modENCODE worm datasets.
Serves for bisulfite sequencing analysis. QUMA suits for bisulfite sequence alignment, trimming raw bisulfite sequence, checking sequence quality, quantifying the methylation profiles by various diagrams and calculation of statistics values. This software consists of two main separate analyses: a methylation status analysis mode using one group of bisulfite sequences and a statistical analysis mode that utilizes two groups of bisulfite sequences.
Produces a pattern representing mark distributions around all of the regions. HebbPlot uses a Hebb network to learn how a mark is distributed around a set of regions that have the same function. It assists biologist in characterization and visualization of chromatin signatures in numerous studies. It generates a digitized image representing the learned signature.
Performs enrichment analyses on epigenomic data for human and mouse genomes. EpiAnnotator provides thousands of annotations for enabling researchers to conduct comparative enrichment analyses and generate their own results in the form of comprehensive publication quality figures. The interface has been designed to be compatible with both computer screen and smartphone displays.
Assists in manipulating both genomic information files and next-generation sequencing (NGS) datasets. NGS++ permits users to integrate new formats and to perform prototyping of functionalities with a focus on the analysis of genomic regions and features. It is composed of three main components: (1) file format management, (2) data manipulation and (3) functional operators.
Identifies regions with epigenomic features specific to combinations of tissue or cell types. EpiCompare can identify regulatory elements such as enhancers, promoters and regions occupied by epigenetic features that are unique to a specific tissue or cell type, as well as those that are shared by multiple tissue and cell types. User can investigate Roadmap Epigenomics data or upload their own data for comparison.
Infers (hydroxy-)methylation levels and efficiencies of the involved enzymes at a certain DNA locus. H(O)TA is based on the construction of two coupled Hidden Markov Models (HMMs). It is able to take into account all relevant conversion errors. This tool predicts only the methylation levels and efficiencies, merged with the corresponding unknown hydroxylation values, of a given region. It is capable of analyzing time course data from hairpin bisulfite sequencing and hairpin oxidative bisulfite sequencing in the same time.
Allows users to perform pairwise correlations of several epigenomic datasets. epiGeEC is an application leaning on the exploitation of intermediate files to compare multiple datasets. This program aims to increase the speed of calculation and allows users to confront their sets to public epigenomic ones. Besides, it enables the calculation of correlations at various resolutions on predefined filtered regions and the annotation and analysis of the generated correlation matrices.
Provides a simulation tool to generate multi-omics data. OmicsSMILA leans on two main modules: SeqSIMLA and pWGBSSimla. SeqSIMLA allows users to simulate sequence data in families with various parameters for sibling and case-control samples and under different disease models. pWGBSSimla focuses on whole-genome DNA methylation data simulation by modeling methylation quantitative trait loci, allele-specific methylations and differentially methylated regions. This tool is available as a desktop and a web-application version.
Aims to estimate the causal single nucleotide polymorphism (SNP) and the causal mark within a gene region that are influencing expression of a given gene. Pathfinder models the hierarchical relationships between genome, chromatin, and gene expression. It is based on a hierarchical statistical method. This method generates well-calibrated posterior probabilities and can prioritize SNPs and marks for functional validation.
Determines mitotic age of a tissue using the quantity of DNA methylation. MiAge Calculator employs the stochastic replication errors accumulated during cell divisions to proceed. It furnishes a panel of more than 250 selected informative CpGs. This tool provides the parameter estimates of the rate of de novo methylation, rate of the fidelity of methylation maintenance, and the methylation level in the starting methylation state of the CpGs.
Detects epigenetic motifs without the need for high-coverage, clonal samples or complete references. EMMCKmer provides a complete framework for using epigenetic profiles as an alternative metric for metagenomics sample comparison. This algorithm has the potential to substantially reduce contig fragmentation and improve clustering of contigs (especially in the case of novel genomes with poor annotation).
Determines variability in microarrays data. VERA is an utility that employs information from replicate microarray experiments to create information depicting its variability according five parameters including the computation of the standard deviation or correlation between multiplicative errors. The software is a part of an approach which aims to investigate difference between gene expressions in cells population by the use of microarray data.
Assists users in identifying differentially-expressed genes. SAM is an approach that attach a value to each gene contained in the studied data corresponding to probability for the gene to be differentially express from one cell population to another. The application can be used in conjunction with VERA software to apply a method dedicated to the detection of difference between gene expressions in cells population by the use of microarray data.
Studies the nuclear organization during interphase. DiGiovanni_DiStefano_FC is an experimental system to test the functional relevance of nuclear organization and the global role of chromosomal rearrangements on various aspects of cell physiology.
Generates cell differentiation associated with heatmaps highlighting important candidate cis-regulatory elements (ccRE) clusters for lineage specific epigenetic events and their associated functions. Snapshot is based on a model-free clustering approach that doesn’t need a predetermined number of clusters which can detect all abundant ccRE clusters. It offers individual index-set data visualization that enables users to combine ccRE clusters with annotations.
Allows users to perform cross-species epigenome mapping. This pipeline leans on reference human and mouse epigenome maps for retaining cell type specific regulatory patterns across species as well as for enabling tissue-specific inference of gene expression. It aims to assist users in enhancing knowledge about epigenome data related to non-model organisms. This program was tested on 12 mammalian and one avian.
Allows visualization of specialized sequencing data in epigenomics. Epigenomics in JBrowse is a collection of plugins designed for JBrowe. It includes visualizing base modifications and small RNAs as well as stranded-coverage tracks and sequence motif density. This tool permits users to visualize the quantity of 4mC, 5mC, 5hmC, and 6mA at single base-pair resolution. It offers several filtering options including by sequence context and base modification.
Displays sequencing data from Roadmap Epigenomics project, powered by a local mirror of UCSC Genome Browser. VizHub is a visualization tool. The Roadmap Epigenomics Mapping Consortium was launched with the goal of producing a public resource of human epigenomic data to catalyze basic biology and disease-oriented research. The Consortium is also committed to the development, standardization and dissemination of protocols, reagents and analytical tools to enable the research community to utilize, integrate and expand upon this body of data.
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