Literature DB >> 22228021

Characterizing and interpreting genetic variation from personal genome sequencing.

Anna C V Johansson1, Lars Feuk.   

Abstract

Since the completion of the human genome project, there has been enormous progress in the development of novel technologies for DNA sequencing. The advent of next-generation sequencing technologies now makes it possible to sequence an entire human genome in one or a few experiments. As a consequence, several individual human genomes have now been fully sequenced, using different experimental strategies. Although the protocols differ between the various sequencing technologies, the challenges of analyzing the data, calling variation, and interpreting the results are similar for all platforms. Here, we give an overview of the human genome sequencing projects completed to date. The strategies for aligning sequence reads and extracting information about different types of genetic variation from the sequence data are discussed. Identification of structural variation, such as copy number variation and insertion-deletion variants, can be complex, and there are a plethora of algorithms and analysis tools available. We also give an overview of the challenge of interpreting the whole-genome sequence data both from a technical and clinical perspective.

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Mesh:

Year:  2012        PMID: 22228021     DOI: 10.1007/978-1-61779-507-7_17

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  4 in total

Review 1.  Whole-genome and whole-exome sequencing in neurological diseases.

Authors:  Jia-Nee Foo; Jian-Jun Liu; Eng-King Tan
Journal:  Nat Rev Neurol       Date:  2012-07-31       Impact factor: 42.937

Review 2.  Next-generation sequencing diagnostics for neurological diseases/disorders: from a clinical perspective.

Authors:  Jia Nee Foo; Jianjun Liu; Eng-King Tan
Journal:  Hum Genet       Date:  2013-03-23       Impact factor: 4.132

Review 3.  Multiomics tools for the diagnosis and treatment of rare neurological disease.

Authors:  L M Crowther; M Poms; Barbara Plecko
Journal:  J Inherit Metab Dis       Date:  2018-03-13       Impact factor: 4.982

4.  Incidental genetic findings in randomized clinical trials: recommendations from the Genomics and Randomized Trials Network (GARNET).

Authors:  Ebony B Bookman; Corina Din-Lovinescu; Bradford B Worrall; Teri A Manolio; Siiri N Bennett; Cathy Laurie; Daniel B Mirel; Kimberly F Doheny; Garnet L Anderson; Kate Wehr; Richard Weinshilboum; Donna T Chen
Journal:  Genome Med       Date:  2013-01-30       Impact factor: 11.117

  4 in total

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