The combination of massive parallel sequencing with a variety of modern DNA/RNA enrichment technologies provides means for interrogating functional protein–genome interactions (ChIP-seq), genome-wide transcriptional activity (RNA-seq; GRO-seq), chromatin accessibility (DNase-seq, FAIRE-seq, MNase-seq), and more recently the three-dimensional organization of chromatin (Hi-C, ChIA-PET). In systems biology-based approaches several of these readouts are generally cumulated with the aim of describing living systems through a reconstitution of the genome-regulatory functions. However, an issue that is often underestimated is that conclusions drawn from such multidimensional analyses of NGS-derived datasets critically depend on the quality of the compared datasets. To address this problem, we have developed the NGS-QC Generator, a quality control system that infers quality descriptors for any kind of ChIP-sequencing and related datasets. In this chapter we provide a detailed protocol for (1) assessing quality descriptors with the NGS-QC Generator; (2) to interpret the generated reports; and (3) to explore the database of QC indicators (www.ngs-qc.org) for >21,000 publicly available datasets.
Next-generation sequencing Massive parallel sequencing Quality control ChIP-sequencing Galaxy Database
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This work was supported by funds from SATT/Conectus, the Fondation pour la Recherche Médicale (FRM), the Alliance Nationale pour les Sciences de la Vie et de la Santé–Institut Thématique Multi-organismes Cancer–Institut National du Cancer (INCa) grant “Epigenomics of breast cancer” and “EpiPCa,” the Ligue National Contre le Cancer (to H.G.; Equipe Labellisée).
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1.Equipe Labellisée Ligue Contre le Cancer, Department of Functional Genomics and CancerInstitut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC)/CNRS/INSERM/Université de StrasbourgIllkirch CedexFrance