| Literature DB >> 27008019 |
Marco Antonio Mendoza-Parra1, Mohamed-Ashick M Saleem2, Matthias Blum2, Pierre-Etienne Cholley2, Hinrich Gronemeyer2.
Abstract
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.Entities:
Keywords: ChIP-sequencing; Database; Galaxy; Massive parallel sequencing; Next-generation sequencing; Quality control
Mesh:
Year: 2016 PMID: 27008019 DOI: 10.1007/978-1-4939-3578-9_13
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745