NGS-QC Generator: A Quality Control System for ChIP-Seq and Related Deep Sequencing-Generated Datasets.
Fiche publication
Date publication
janvier 2016
Journal
Methods in molecular biology (Clifton, N.J.)
Auteurs
Membres identifiés du Cancéropôle Est :
Dr GRONEMEYER Hinrich
Tous les auteurs :
Mendoza-Parra MA, Saleem MA, Blum M, Cholley PE, Gronemeyer H
Lien Pubmed
Résumé
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.
Mots clés
Chromatin Immunoprecipitation, methods, Computational Biology, methods, Databases, Genetic, Genomics, methods, High-Throughput Nucleotide Sequencing, methods, Humans, Quality Control, Sequence Analysis, DNA, methods, Software, Web Browser
Référence
Methods Mol. Biol.. 2016 ;1418:243-65