发明名称 Systems and methods for genomic annotation and distributed variant interpretation
摘要 A computer-based genomic annotation system, including a database configured to store genomic data, non-transitory memory configured to store instructions, and at least one processor coupled with the memory, the processor configured to implement the instructions in order to implement an annotation pipeline and at least one module filtering or analysis of the genomic data.
申请公布号 US9600627(B2) 申请公布日期 2017.03.21
申请号 US201514614899 申请日期 2015.02.05
申请人 The Scripps Research Institute 发明人 Torkamani Ali;Schork Nicholas
分类号 G06F17/30;G06F7/00;G06F19/24;G06F19/18 主分类号 G06F17/30
代理机构 Knobbe, Martens, Olson & Bear, LLP 代理人 Knobbe, Martens, Olson & Bear, LLP
主权项 1. A computer-based genomic annotation system, comprising: non-transitory memory configured to store instructions, and at least one hardware processor coupled with the memory, the hardware processor configured to: receive a variant file, the variant file being populated with a plurality of genomic DNA variants relative to a reference genomic DNA sequence, the plurality of variants comprising at least a reported first variant, a novel second variant, and a novel third variant that have been found in the genome of a subject; generate an annotation file, the annotation file defining a plurality of annotation categories corresponding to selected characteristics of genomic variants; generate a plurality of annotations for the first variant, wherein generating the plurality of annotations for the first variant comprises: retrieving a reported causal association between the first variant and a phenotype;generating at least one annotation based at least in part on the reported causal association;selecting a first predicted clinical relevance categorization of the first variant based at least in part on the reported causal association between the first variant and a phenotype; andgenerating at least one annotation based at least in part on the first predicted clinical relevance categorization; generate a plurality of annotations for the second variant, wherein generating the plurality of annotations for the second variant comprises: retrieving the identity of a gene nearest the second variant;generating at least one annotation based at least in part on the identity;retrieving a reported association between the gene nearest the second variant and a phenotype;generating at least one annotation based at least in part on the reported association;generating a computationally predicted functional impact of the second variant with respect to the identified gene;generating at least one annotation based at least in part on the computationally predicted functional impact;selecting a second predicted clinical relevance categorization that is different from the first predicted clinical relevance categorization, wherein the selection is based at least in part on the computationally predicted functional impact of the second variant with respect to the gene nearest the second variant; andgenerating at least one annotation based on the selected second clinical relevance categorization; generate a plurality of annotations for the third variant, wherein generating the plurality of annotations for the third variant comprises: retrieving the identity of a gene nearest the third variant and generating at least one annotation based at least in part on the identity,retrieving a reported association between the gene nearest the third variant and a phenotype and generating at least one annotation based at least in part on the reported association,generating a computationally predicted functional impact of the third variant with respect to the gene nearest the third variant that is less severe than the computationally predicted functional impact of the second variant with respect to the gene nearest the second variant;generating at least one annotation based at least in part on the computationally predicted functional impact of the third variant with respect to the gene nearest the third variant, andselecting a third predicted clinical relevance categorization different from the first and the second predicted clinical relevance categorizations, wherein the selection is based at least in part on the computationally predicted functional impact of the third variant with respect to the gene nearest the third variant; andgenerating at least one annotation based at least in part on the selected third clinical relevance categorization; populate the annotation file with the plurality of generated annotations; and deliver variant specific information about the plurality of genomic DNA variants using the populated annotation file.
地址 La Jolla CA US