title: Technology-specific error signatures in the 1000 Genomes Project data.
abstract: Next-generation sequencing (NGS) will likely facilitate a better understanding of the causes and consequences of human genetic variability. In this context, the validity of NGS-inferred single-nucleotide variants (SNVs) is of paramount importance. We therefore developed a statistical framework to assess the fidelity of three common NGS platforms. Using aligned DNA sequence data from two completely sequenced HapMap samples as included in the 1000 Genomes Project, we unraveled remarkably different error profiles for the three platforms. Compared to confirmed HapMap variants, newly identified SNVs included a substantial proportion of false positives (3-17%). Consensus calling by more than one platform yielded significantly lower error rates (1-4%). This implies that the use of multiple NGS platforms may be more cost-efficient than relying upon a single technology alone, particularly in physically localized sequencing experiments that rely upon small error rates. Our study thus highlights that different NGS platforms suit different practical applications differently well, and that NGS-based studies require stringent data quality control for their results to be valid.
authors.affiliation: Institute of Medical Informatics and Statistics, Christian-Albrechts University, Brunswiker Str. 10, 24105 Kiel, Germany, nothnagel@medinfo.uni-kiel.de
authors.forename: Michael
authors.initials: M
authors.lastname: Nothnagel
authors.forename: Alexander
authors.initials: A
authors.lastname: Herrmann
authors.forename: Andreas
authors.initials: A
authors.lastname: Wolf
authors.forename: Stefan
authors.initials: S
authors.lastname: Schreiber
authors.forename: Matthias
authors.initials: M
authors.lastname: Platzer
authors.forename: Reiner
authors.initials: R
authors.lastname: Siebert
authors.forename: Michael
authors.initials: M
authors.lastname: Krawczak
authors.forename: Jochen
authors.initials: J
authors.lastname: Hampe
mesh_terms: D000465:Algorithms; D016477:Artifacts; D014644:Genetic Variation; D015894:Genome, Human; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D016045:Human Genome Project; D006801:Humans; D011786:Quality Control; D017422:Sequence Analysis, DNA / Q000379:methods / Q000592:standards* / Q000706:statistics & numerical data*