SPDI: data model for variants and applications at NCBI.

ABSTRACT:

Motivation

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.

Results

The SPDI data model defines variants as a sequence of four attributes: sequence, position, deletion and insertion, and can be applied to nucleotide and protein variants. NCBI web services convert representations among HGVS, VCF and SPDI and provide two functions to

SUBMITTER: Holmes JB 

PROVIDER: S-EPMC7523648 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature