title: Repetitive DNA and next-generation sequencing: computational challenges and solutions.
abstract: Repetitive DNA sequences are abundant in a broad range of species, from bacteria to mammals, and they cover nearly half of the human genome. Repeats have always presented technical challenges for sequence alignment and assembly programs. Next-generation sequencing projects, with their short read lengths and high data volumes, have made these challenges more difficult. From a computational perspective, repeats create ambiguities in alignment and assembly, which, in turn, can produce biases and errors when interpreting results. Simply ignoring repeats is not an option, as this creates problems of its own and may mean that important biological phenomena are missed. We discuss the computational problems surrounding repeats and describe strategies used by current bioinformatics systems to solve them.
authors: McKusick-Nathans Institute for Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland                 21205, USA.
authors: Todd J
authors: TJ
authors: Treangen
authors: Steven L
authors: SL
authors: Salzberg
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D004247:DNA / Q000235:genetics; D016678:Genome / Q000235:genetics; D006801:Humans; D008969:Molecular Sequence Data; D010944:Plants; D012313:RNA / Q000235:genetics; D012091:Repetitive Sequences, Nucleic Acid / Q000235:genetics; D015203:Reproducibility of Results; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods / Q000639:trends; D017423:Sequence Analysis, RNA / Q000379:methods / Q000639:trends; D012984:Software
chemical_list: D012313:RNA; D004247:DNA