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      A quality control system for profiles obtained by ChIP sequencing

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          Abstract

          The absence of a quality control (QC) system is a major weakness for the comparative analysis of genome-wide profiles generated by next-generation sequencing (NGS). This concerns particularly genome binding/occupancy profiling assays like chromatin immunoprecipitation (ChIP-seq) but also related enrichment-based studies like methylated DNA immunoprecipitation/methylated DNA binding domain sequencing, global run on sequencing or RNA-seq. Importantly, QC assessment may significantly improve multidimensional comparisons that have great promise for extracting information from combinatorial analyses of the global profiles established for chromatin modifications, the bindings of epigenetic and chromatin-modifying enzymes/machineries, RNA polymerases and transcription factors and total, nascent or ribosome-bound RNAs. Here we present an approach that associates global and local QC indicators to ChIP-seq data sets as well as to a variety of enrichment-based studies by NGS. This QC system was used to certify >5600 publicly available data sets, hosted in a database for data mining and comparative QC analyses.

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          Most cited references18

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          Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences

          Increased reliance on computational approaches in the life sciences has revealed grave concerns about how accessible and reproducible computation-reliant results truly are. Galaxy http://usegalaxy.org, an open web-based platform for genomic research, addresses these problems. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Pages are interactive, web-based documents that provide users with a medium to communicate a complete computational analysis.
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            Principles and challenges of genomewide DNA methylation analysis.

            Methylation of cytosine bases in DNA provides a layer of epigenetic control in many eukaryotes that has important implications for normal biology and disease. Therefore, profiling DNA methylation across the genome is vital to understanding the influence of epigenetics. There has been a revolution in DNA methylation analysis technology over the past decade: analyses that previously were restricted to specific loci can now be performed on a genome-scale and entire methylomes can be characterized at single-base-pair resolution. However, there is such a diversity of DNA methylation profiling techniques that it can be challenging to select one. This Review discusses the different approaches and their relative merits and introduces considerations for data analysis.
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              Chromosome-wide and promoter-specific analyses identify sites of differential DNA methylation in normal and transformed human cells.

              Cytosine methylation is required for mammalian development and is often perturbed in human cancer. To determine how this epigenetic modification is distributed in the genomes of primary and transformed cells, we used an immunocapturing approach followed by DNA microarray analysis to generate methylation profiles of all human chromosomes at 80-kb resolution and for a large set of CpG islands. In primary cells we identified broad genomic regions of differential methylation with higher levels in gene-rich neighborhoods. Female and male cells had indistinguishable profiles for autosomes but differences on the X chromosome. The inactive X chromosome (Xi) was hypermethylated at only a subset of gene-rich regions and, unexpectedly, overall hypomethylated relative to its active counterpart. The chromosomal methylation profile of transformed cells was similar to that of primary cells. Nevertheless, we detected large genomic segments with hypomethylation in the transformed cell residing in gene-poor areas. Furthermore, analysis of 6,000 CpG islands showed that only a small set of promoters was methylated differentially, suggesting that aberrant methylation of CpG island promoters in malignancy might be less frequent than previously hypothesized.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                November 2013
                14 September 2013
                14 September 2013
                : 41
                : 21
                : e196
                Affiliations
                Department of Cancer Biology, Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC)/CNRS/INSERM/Université de Strasbourg, BP 10142, 67404 Illkirch Cedex, France
                Author notes
                *To whom correspondence should be addressed. Tel: +33 3 88 65 34 73; Fax: +33 3 88 65 34 37; Email: hg@ 123456igbmc.u-strasbg.fr
                Correspondence may also be addressed to Marco-Antonio Mendoza-Parra. Tel: +33 3 88 65 34 19; Fax: +33 3 88 65 34 37; Email: marco@ 123456igbmc.fr
                Article
                gkt829
                10.1093/nar/gkt829
                3834836
                24038469
                e9bf5b57-ea61-48bb-b20a-598fa93e884c
                © The Author(s) 2013. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 3 November 2012
                : 14 August 2013
                : 25 August 2013
                Page count
                Pages: 13
                Categories
                Methods Online

                Genetics
                Genetics

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