NGS-QC Generator: A Quality Control System for ChIP-Seq and Related Deep Sequencing-Generated Datasets
| Autor: | Mohamed-Ashick M. Saleem, Marco Antonio Mendoza-Parra, Pierre-Etienne Cholley, Hinrich Gronemeyer, Matthias Blum |
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| Přispěvatelé: | Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut de génétique et biologie moléculaire et cellulaire (IGBMC), Université Louis Pasteur - Strasbourg I-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Protocol (science) Massive parallel sequencing 030102 biochemistry & molecular biology Computer science Systems biology genetic processes RNA Genomics computer.software_genre [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM] DNA sequencing Deep sequencing Chromatin ChIP-sequencing 03 medical and health sciences chemistry.chemical_compound 030104 developmental biology chemistry natural sciences Data mining Chromatin immunoprecipitation computer DNA Generator (mathematics) |
| Zdroj: | Methods in Molecular Biology Methods in Molecular Biology, 1418, Humana Press, pp.243-65, 2016, Methods in Molecular Biology, ⟨10.1007/978-1-4939-3578-9_13⟩ Methods in Molecular Biology ISBN: 9781493935765 Statistical Genomics |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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