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      SPDI: data model for variants and applications at NCBI.

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          Abstract

          Normalizing sequence variants on a reference, projecting them across congruent sequences and aggregating their diverse representations are critical to the elucidation of the genetic basis of disease and biological function. Inconsistent representation of variants among variant callers, local databases and tools result in discrepancies that complicate analysis. NCBI's genetic variation resources, dbSNP and ClinVar, require a robust, scalable set of principles to manage asserted sequence variants.

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          Author and article information

          Journal
          Bioinformatics
          Bioinformatics (Oxford, England)
          Oxford University Press (OUP)
          1367-4811
          1367-4803
          March 01 2020
          : 36
          : 6
          Affiliations
          [1 ] Information Engineering Branch, National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH), Bethesda, MD 20894, USA.
          Article
          5628222
          10.1093/bioinformatics/btz856
          7523648
          31738401
          b698c268-4c7d-4a03-9db2-a05135202a95
          History

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