title: Next generation sequencing methodologies--an overview.
abstract: Gene discovery has been one of the most important advances in our understanding of human disorders. Early linkage and positional cloning strategies have now given way to next generation sequencing (NGS) with age-old help from biostatistical and bioinformatical input. In this chapter, we present the importance of getting the basics right, namely, how the best phenotyping in the clinical domain will provide a higher chance of a successful NGS experiment. In addition, we show getting the correct submission of DNA samples to NGS providers is dependent on the type of inheritance pattern that may or may not be apparent. We discuss one of the most crucial decisions for investigators when designing a study, namely choosing a trio, quad or cohort for analysis. Following on from this, we compare and contrast the underlying technology adopted by provider companies as they vie for customers and submissions. Each platform has advantages and disadvantages based on false calls, coverage, and read depth; however, some of these issues may be solved with the third wave of sequencing technology development in early commercial roll-out. Lastly, we provide a bioinformatic filtering overview of a "quad"-based submission and show how 3 million SNPs and indels can be reduced to a biologically plausible and experimentally manageable n≤50 gene variants.
authors.affiliation: Neurology Research and Molecular Neuroscience, Institute of Life Science, College of Medicine, Swansea University, Swansea, UK.
authors.forename: William O
authors.initials: WO
authors.lastname: Pickrell
authors.forename: Mark I
authors.initials: MI
authors.lastname: Rees
authors.forename: Seo-Kyung
authors.initials: SK
authors.lastname: Chung
mesh_terms: D000818:Animals; D019295:Computational Biology; D006801:Humans; D010641:Phenotype; D011506:Proteins / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000295:instrumentation / Q000379:methods* / Q000639:trends*
chemical_list: D011506:Proteins