Dataset Information

ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia.

ABSTRACT: Chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) has become a valuable and widely used approach for mapping the genomic location of transcription-factor binding and histone modifications in living cells. Despite its widespread use, there are considerable differences in how these experiments are conducted, how the results are scored and evaluated for quality, and how the data and metadata are archived for public use. These practices affect the quality and utility of any global ChIP experiment. Through our experience in performing ChIP-seq experiments, the ENCODE and modENCODE consortia have developed a set of working standards and guidelines for ChIP experiments that are updated routinely. The current guidelines address antibody validation, experimental replication, sequencing depth, data and metadata reporting, and data quality assessment. We discuss how ChIP quality, assessed in these ways, affects different uses of ChIP-seq data. All data sets used in the analysis have been deposited for public viewing and downloading at the ENCODE (http://encodeproject.org/ENCODE/) and modENCODE (http://www.modencode.org/) portals.

SUBMITTER: Landt SG

PROVIDER: S-EPMC3431496 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia.

Landt Stephen G SG Marinov Georgi K GK Kundaje Anshul A Kheradpour Pouya P Pauli Florencia F Batzoglou Serafim S Bernstein Bradley E BE Bickel Peter P Brown James B JB Cayting Philip P Chen Yiwen Y DeSalvo Gilberto G Epstein Charles C Fisher-Aylor Katherine I KI Euskirchen Ghia G Gerstein Mark M Gertz Jason J Hartemink Alexander J AJ Hoffman Michael M MM Iyer Vishwanath R VR Jung Youngsook L YL Karmakar Subhradip S Kellis Manolis M Kharchenko Peter V PV Li Qunhua Q Liu Tao T Liu X Shirley XS Ma Lijia L Milosavljevic Aleksandar A Myers Richard M RM Park Peter J PJ Pazin Michael J MJ Perry Marc D MD Raha Debasish D Reddy Timothy E TE Rozowsky Joel J Shoresh Noam N Sidow Arend A Slattery Matthew M Stamatoyannopoulos John A JA Tolstorukov Michael Y MY White Kevin P KP Xi Simon S Farnham Peggy J PJ Lieb Jason D JD Wold Barbara J BJ Snyder Michael M

Genome research 20120901 9

Chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) has become a valuable and widely used approach for mapping the genomic location of transcription-factor binding and histone modifications in living cells. Despite its widespread use, there are considerable differences in how these experiments are conducted, how the results are scored and evaluated for quality, and how the data and metadata are archived for public use. These practices affect the quality and ...[more]

PMID: 22955991

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Project description:Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-seq) or ChIP followed by genome tiling array analysis (ChIP-chip) have become standard technologies for genome-wide identification of DNA-binding protein target sites. A number of algorithms have been developed in parallel that allow identification of binding sites from ChIP-seq or ChIP-chip datasets and subsequent visualization in the University of California Santa Cruz (UCSC) Genome Browser as custom annotation tracks. However, summarizing these tracks can be a daunting task, particularly if there are a large number of binding sites or the binding sites are distributed widely across the genome.We have developed ChIPpeakAnno as a Bioconductor package within the statistical programming environment R to facilitate batch annotation of enriched peaks identified from ChIP-seq, ChIP-chip, cap analysis of gene expression (CAGE) or any experiments resulting in a large number of enriched genomic regions. The binding sites annotated with ChIPpeakAnno can be viewed easily as a table, a pie chart or plotted in histogram form, i.e., the distribution of distances to the nearest genes for each set of peaks. In addition, we have implemented functionalities for determining the significance of overlap between replicates or binding sites among transcription factors within a complex, and for drawing Venn diagrams to visualize the extent of the overlap between replicates. Furthermore, the package includes functionalities to retrieve sequences flanking putative binding sites for PCR amplification, cloning, or motif discovery, and to identify Gene Ontology (GO) terms associated with adjacent genes.ChIPpeakAnno enables batch annotation of the binding sites identified from ChIP-seq, ChIP-chip, CAGE or any technology that results in a large number of enriched genomic regions within the statistical programming environment R. Allowing users to pass their own annotation data such as a different Chromatin immunoprecipitation (ChIP) preparation and a dataset from literature, or existing annotation packages, such as GenomicFeatures and BSgenome, provides flexibility. Tight integration to the biomaRt package enables up-to-date annotation retrieval from the BioMart database.

Dataset Information

ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia.

Publications

ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia.

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