ArticleBMC bioinformatics2011
An integrated ChIP-seq analysis platform with customizable workflows.
Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.
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Who cites it
64 citing papers in PubMed.
- ChEAP: ChIP-exo analysis pipeline and the investigation ofComputational and structural biotechnology journal · 2023Article
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- Scaffold association factor B (SAFB) is required for expression of prenyltransferases and RAS membrane association.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
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- Crunch: integrated processing and modeling of ChIP-seq data in terms of regulatory motifs.Genome research · 2019Article
- Rational Targeting of Cooperating Layers of the Epigenome Yields Enhanced Therapeutic Efficacy against AML.Cancer discovery · 2019Article
- MEF2B Instructs Germinal Center Development and Acts as an Oncogene in B Cell Lymphomagenesis.Cancer cell · 2018Article
- Integrative analysis of methylomic and transcriptomic data in fetal sheep muscle tissues in response to maternal diet during pregnancy.BMC genomics · 2018Article
- AICDA drives epigenetic heterogeneity and accelerates germinal center-derived lymphomagenesis.Nature communications · 2018Article
- TET proteins safeguard bivalent promoters from de novo methylation in human embryonic stem cells.Nature genetics · 2018Article
- Analyzing DNA Methylation Patterns During Tumor Evolution.Methods in molecular biology (Clifton, N.J.) · 2018Article
- High-intensity UV laser ChIP-seq for the study of protein-DNA interactions in living cells.Nature communications · 2017Article
- Epigenetic Identity in AML Depends on Disruption of Nonpromoter Regulatory Elements and Is Affected by Antagonistic Effects of Mutations in Epigenetic Modifiers.Cancer discovery · 2017Article
- Genome-wide analysis of DNA methylation in hypothalamus and ovary of Capra hircus.BMC genomics · 2017Article
- ORIO (Online Resource for Integrative Omics): a web-based platform for rapid integration of next generation sequencing data.Nucleic acids research · 2017Article
- Common nonmutationalProceedings of the National Academy of Sciences of the United States of America · 2017Article
- The CREBBP Acetyltransferase Is a Haploinsufficient Tumor Suppressor in B-cell Lymphoma.Cancer discovery · 2017Article
- CREBBP Inactivation Promotes the Development of HDAC3-Dependent Lymphomas.Cancer discovery · 2017Article
- ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline.BMC bioinformatics · 2016Article
- Article
4 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChromatin immunoprecipitation followed by next generation sequencing (ChIP-seq), enables unbiased and genome-wide mapping of protein-DNA interactions and epigenetic marks. The first step in ChIP-seq data analysis involves the identification of peaks (i.e., genomic locations with high density of mapped sequence reads). The next step consists of interpreting the biological meaning of the peaks through their association with known genes, pathways, regulatory elements, and integration with other experiments. Although several programs have been published for the analysis of ChIP-seq data, they often focus on the peak detection step and are usually not well suited for thorough, integrative analysis of the detected peaks.
resultsTo address the peak interpretation challenge, we have developed ChIPseeqer, an integrative, comprehensive, fast and user-friendly computational framework for in-depth analysis of ChIP-seq datasets. The novelty of our approach is the capability to combine several computational tools in order to create easily customized workflows that can be adapted to the user's needs and objectives. In this paper, we describe the main components of the ChIPseeqer framework, and also demonstrate the utility and diversity of the analyses offered, by analyzing a published ChIP-seq dataset.
conclusionsChIPseeqer facilitates ChIP-seq data analysis by offering a flexible and powerful set of computational tools that can be used in combination with one another. The framework is freely available as a user-friendly GUI application, but all programs are also executable from the command line, thus providing flexibility and automatability for advanced users.
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