Dataset Information

Variable reproducibility in genome-scale public data: A case study using ENCODE ChIP sequencing resource.

ABSTRACT: Genome-wide data is accumulating in an unprecedented way in the public domain. Re-mining this data shows great potential to generate novel hypotheses. However this approach is dependent on the quality (technical and biological) of the underlying data. Here we performed a systematic analysis of chromatin immunoprecipitation (ChIP) sequencing data of transcription and epigenetic factors from the encyclopaedia of DNA elements (ENCODE) resource to demonstrate that about one third of conditions with replicates show low concordance between replicate peak lists. This serves as a case study to demonstrate a caveat concerning genome-wide analyses and highlights a need to validate the quality of each sample before performing further associative analyses.

SUBMITTER: Devailly G

PROVIDER: S-EPMC4686001 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Publications

Variable reproducibility in genome-scale public data: A case study using ENCODE ChIP sequencing resource.

Devailly Guillaume G Mantsoki Anna A Michoel Tom T Joshi Anagha A

FEBS letters 20151124 24 Pt B

Genome-wide data is accumulating in an unprecedented way in the public domain. Re-mining this data shows great potential to generate novel hypotheses. However this approach is dependent on the quality (technical and biological) of the underlying data. Here we performed a systematic analysis of chromatin immunoprecipitation (ChIP) sequencing data of transcription and epigenetic factors from the encyclopaedia of DNA elements (ENCODE) resource to demonstrate that about one third of conditions with ...[more]

PMID: 26619763

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Project description:ChIP-seq has become the primary method for identifying in vivo protein-DNA interactions on a genome-wide scale, with nearly 800 publications involving the technique appearing in PubMed as of December 2012. Individually and in aggregate, these data are an important and information-rich resource. However, uncertainties about data quality confound their use by the wider research community. Recently, the Encyclopedia of DNA Elements (ENCODE) project developed and applied metrics to objectively measure ChIP-seq data quality. The ENCODE quality analysis was useful for flagging datasets for closer inspection, eliminating or replacing poor data, and for driving changes in experimental pipelines. There had been no similarly systematic quality analysis of the large and disparate body of published ChIP-seq profiles. Here, we report a uniform analysis of vertebrate transcription factor ChIP-seq datasets in the Gene Expression Omnibus (GEO) repository as of April 1, 2012. The majority (55%) of datasets scored as being highly successful, but a substantial minority (20%) were of apparently poor quality, and another ?25% were of intermediate quality. We discuss how different uses of ChIP-seq data are affected by specific aspects of data quality, and we highlight exceptional instances for which the metric values should not be taken at face value. Unexpectedly, we discovered that a significant subset of control datasets (i.e., no immunoprecipitation and mock immunoprecipitation samples) display an enrichment structure similar to successful ChIP-seq data. This can, in turn, affect peak calling and data interpretation. Published datasets identified here as high-quality comprise a large group that users can draw on for large-scale integrated analysis. In the future, ChIP-seq quality assessment similar to that used here could guide experimentalists at early stages in a study, provide useful input in the publication process, and be used to stratify ChIP-seq data for different community-wide uses.

Dataset Information

Variable reproducibility in genome-scale public data: A case study using ENCODE ChIP sequencing resource.

Publications

Variable reproducibility in genome-scale public data: A case study using ENCODE ChIP sequencing resource.

Similar Datasets

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