EpiGRAPH: User-friendly software for statistical analysis and prediction of (epi-) genomic data

Max-Planck-Institut für Informatik, Campus E1.4, 66123 Saarbrücken, Germany.
Genome biology (Impact Factor: 10.81). 03/2009; 10(2):R14. DOI: 10.1186/gb-2009-10-2-r14
Source: PubMed


The EpiGRAPH web service enables biologists to uncover hidden associations in vertebrate genome and epigenome datasets. Users can upload sets of genomic regions and EpiGRAPH will test multiple attributes (including DNA sequence, chromatin structure, epigenetic modifications and evolutionary conservation) for enrichment or depletion among these regions. Furthermore, EpiGRAPH learns to predictively identify similar genomic regions. This paper demonstrates EpiGRAPH's practical utility in a case study on monoallelic gene expression and describes its novel approach to reproducible bioinformatic analysis.

Download full-text


Available from: Konstantin Halachev
  • Source
    • "(D) Functional and structural characteristics of the 1000 most variable genes in terms of DNA methylation (left) and gene expression (right). Functional annotation clustering was performed with the DAVID software (Huang et al., 2007), and the promoter characteristics were analyzed by the EpiGRAPH web service (Bock et al., 2009). This panel provides a summary of the results; the full results tables are available online "
    [Show abstract] [Hide abstract]
    ABSTRACT: The developmental potential of human pluripotent stem cells suggests that they can produce disease-relevant cell types for biomedical research. However, substantial variation has been reported among pluripotent cell lines, which could affect their utility and clinical safety. Such cell-line-specific differences must be better understood before one can confidently use embryonic stem (ES) or induced pluripotent stem (iPS) cells in translational research. Toward this goal we have established genome-wide reference maps of DNA methylation and gene expression for 20 previously derived human ES lines and 12 human iPS cell lines, and we have measured the in vitro differentiation propensity of these cell lines. This resource enabled us to assess the epigenetic and transcriptional similarity of ES and iPS cells and to predict the differentiation efficiency of individual cell lines. The combination of assays yields a scorecard for quick and comprehensive characterization of pluripotent cell lines.
    Full-text · Article · Feb 2011 · Cell
  • Source
    • "For example, numerous tools, integrated or not in larger analysis pipelines, have been proposed that allow: annotation of genomic features present in the neighbourhood of the relevant enrichment signals (5–7), detection and de novo definition of consensus DNA motifs (6), cross and compare information from distinct datasets (8) and comprehensive visualization of the obtained GW results (9–11). More recently, sophisticated statistical approaches were proposed to predict association between sets of genomic locations and numerous genomic features (12,13). Nevertheless, due to the multiplicity of biological questions that may be asked by the ChIP-seq method, many analysis issues remain un-addressed. "
    [Show abstract] [Hide abstract]
    ABSTRACT: In a single experiment, chromatin immunoprecipitation combined with high throughput sequencing (ChIP-seq) provides genome-wide information about a given covalent histone modification or transcription factor occupancy. However, time efficient bioinformatics resources for extracting biological meaning out of these gigabyte-scale datasets are often a limiting factor for data interpretation by biologists. We created an integrated portable ChIP-seq data interpretation platform called seqMINER, with optimized performances for efficient handling of multiple genome-wide datasets. seqMINER allows comparison and integration of multiple ChIP-seq datasets and extraction of qualitative as well as quantitative information. seqMINER can handle the biological complexity of most experimental situations and proposes methods to the user for data classification according to the analysed features. In addition, through multiple graphical representations, seqMINER allows visualization and modelling of general as well as specific patterns in a given dataset. To demonstrate the efficiency of seqMINER, we have carried out a comprehensive analysis of genome-wide chromatin modification data in mouse embryonic stem cells to understand the global epigenetic landscape and its change through cellular differentiation.
    Full-text · Article · Dec 2010 · Nucleic Acids Research
  • Source
    • "EpiGRAPH ( is an online software to analyze genomic and epigenomic features enriched in a group of given DNA fragments (35–37). EpiGRAPH was used to analyze DNA sequences harboring the differentially methylated CpG sites in CdLS in terms of the specific DNA sequence patterns, the overlap with specific genomic regions (e.g. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The cohesin complex has recently been shown to be a key regulator of eukaryotic gene expression, although the mechanisms by which it exerts its effects are poorly understood. We have undertaken a genome-wide analysis of DNA methylation in cohesin-deficient cell lines from probands with Cornelia de Lange syndrome (CdLS). Heterozygous mutations in NIPBL, SMC1A and SMC3 genes account for ∼65% of individuals with CdLS. SMC1A and SMC3 are subunits of the cohesin complex that controls sister chromatid cohesion, whereas NIPBL facilitates cohesin loading and unloading. We have examined the methylation status of 27 578 CpG dinucleotides in 72 CdLS and control samples. We have documented the DNA methylation pattern in human lymphoblastoid cell lines (LCLs) as well as identified specific differential DNA methylation in CdLS. Subgroups of CdLS probands and controls can be classified using selected CpG loci. The X chromosome was also found to have a unique DNA methylation pattern in CdLS. Cohesin preferentially binds to hypo-methylated DNA in control LCLs, whereas the differential DNA methylation alters cohesin binding in CdLS. Our results suggest that in addition to DNA methylation multiple mechanisms may be involved in transcriptional regulation in human cells and in the resultant gene misexpression in CdLS.
    Full-text · Article · May 2010 · Nucleic Acids Research
Show more