ArticleGenome biology2009
EpiGRAPH: user-friendly software for statistical analysis and prediction of (epi)genomic data.
Article in Genome biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
28 citing papers in PubMed.
- PretiMeth: precise prediction models for DNA methylation based on single methylation mark.BMC genomics · 2020Article
- Proactive visual and statistical analysis of genomic data in Epiviz.Bioinformatics (Oxford, England) · 2020Article
- Colocalization analyses of genomic elements: approaches, recommendations and challenges.Bioinformatics (Oxford, England) · 2019Article
- Putative functional genes in idiopathic dilated cardiomyopathy.Scientific reports · 2018Article
- GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome.GigaScience · 2017Article
- Computationally expanding infinium HumanMethylation450 BeadChip array data to reveal distinct DNA methylation patterns of rheumatoid arthritis.Bioinformatics (Oxford, England) · 2016Article
- LOLA: enrichment analysis for genomic region sets and regulatory elements in R and Bioconductor.Bioinformatics (Oxford, England) · 2016Article
- Integrating Epigenomics into the Understanding of Biomedical Insight.Bioinformatics and biology insights · 2016Review
- ColoWeb: a resource for analysis of colocalization of genomic features.BMC genomics · 2015Article
- DNA methylation signatures link prenatal famine exposure to growth and metabolism.Nature communications · 2014Article
- Comprehensive analysis of DNA methylation data with RnBeads.Nature methods · 2014Article
- Recommendations for the design and analysis of epigenome-wide association studies.Nature methods · 2013Review
- CpG_MPs: identification of CpG methylation patterns of genomic regions from high-throughput bisulfite sequencing data.Nucleic acids research · 2013Article
- High-resolution mapping of h1 linker histone variants in embryonic stem cells.PLoS genetics · 2013Article
- EpiExplorer: live exploration and global analysis of large epigenomic datasets.Genome biology · 2012Article
- Analysing and interpreting DNA methylation data.Nature reviews. Genetics · 2012Review
- Mutant p53 is a transcriptional co-factor that binds to G-rich regulatory regions of active genes and generates transcriptional plasticity.Cell cycle (Georgetown, Tex.) · 2012Article
- Dynamic CpG island methylation landscape in oocytes and preimplantation embryos.Nature genetics · 2011Article
- Extensive and coordinated transcription of noncoding RNAs within cell-cycle promoters.Nature genetics · 2011Article
- seqMINER: an integrated ChIP-seq data interpretation platform.Nucleic acids research · 2011Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The EpiGRAPH web service http://epigraph.mpi-inf.mpg.de/ 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.
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Registered trials
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