Dataset Information

Using DIVAN to assess disease/trait-associated single nucleotide variants in genome-wide scale.

ABSTRACT: The majority of sequence variants identified by Genome-wide association studies (GWASs) fall outside of the protein-coding regions. Unlike coding variants, it is challenging to connect these noncoding variants to the pathophysiology of complex diseases/traits due to the lack of functional annotations in the non-coding regions. To overcome this, by leveraging the rich collection of genomic and epigenomic profiles, we have developed DIVAN, or Disease/trait-specific Variant ANnotation, which enables the assignment of a measurement (D-score) for each base of the human genome in a disease/trait-specific manner. To facilitate the utilization of DIVAN, we pre-computed D-scores for every base of the human genome (hg19) for 45 different diseases/traits.In this work, we present a detailed protocol on how to utilize DIVAN software toolkit to retrieve D-scores either by variant identifiers or by genomic regions for a disease/trait of interest. We also demonstrate the utilities of the D-scores using real data examples. We believe that the pre-computed D-scores for 45 diseases/traits is a useful resource to follow up on the discoveries made by GWASs, and the DIVAN software toolkit provides a convenient way to access this resource. DIVAN is freely available at https://sites.google.com/site/emorydivan/software .

SUBMITTER: Chen L

PROVIDER: S-EPMC5663107 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Using DIVAN to assess disease/trait-associated single nucleotide variants in genome-wide scale.

Chen Li L Qin Zhaohui S ZS

BMC research notes 20171030 1

<h4>Objective</h4>The majority of sequence variants identified by Genome-wide association studies (GWASs) fall outside of the protein-coding regions. Unlike coding variants, it is challenging to connect these noncoding variants to the pathophysiology of complex diseases/traits due to the lack of functional annotations in the non-coding regions. To overcome this, by leveraging the rich collection of genomic and epigenomic profiles, we have developed DIVAN, or Disease/trait-specific Variant ANnota ...[more]

PMID: 29084591

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Dataset Information

Using DIVAN to assess disease/trait-associated single nucleotide variants in genome-wide scale.

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Using DIVAN to assess disease/trait-associated single nucleotide variants in genome-wide scale.

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