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GPCards: An integrated database of genotype–phenotype correlations in human genetic diseases

机译:GPCards:人类遗传疾病中基因型表型相关性的集成数据库

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Genotype–phenotype correlations are the basis of precision medicine of human genetic diseases. However, it remains a challenge for clinicians and researchers to conveniently access detailed individual-level clinical phenotypic features of patients with various genetic variants. To address this urgent need, we manually searched for genetic studies in PubMed and catalogued 8,309 genetic variants in 1,288 genes from 17,738 patients with detailed clinical phenotypic features from 1,855 publications. Based on genotype–phenotype correlations in this dataset, we developed an user-friendly online database called GPCards ( http://genemed.tech/gpcards/ ), which not only provided the association between genetic diseases and disease genes, but also the prevalence of various clinical phenotypes related to disease genes and the patient-level mapping between these clinical phenotypes and genetic variants. To accelerate the interpretation of genetic variants, we integrated 62 well-known variant-level and gene-level genomic data sources, including functional predictions, allele frequencies in different populations, and disease-related information. Furthermore, GPCards enables automatic analyses of users’ own genetic data, comprehensive annotation, prioritization of candidate functional variants, and identification of genotype–phenotype correlations using custom parameters. In conclusion, GPCards is expected to accelerate the interpretation of genotype–phenotype correlations, subtype classification, and candidate gene prioritisation in human genetic diseases.
机译:基因型 - 表型相关是人遗传疾病精确药物的基础。然而,临床医生和研究人员对各种遗传变异患者的细节临床表型特征仍然是一个挑战。为了解决这一迫切需要,我们手动搜索了来自1,288个基因的Pubmed和目录的8,309个遗传变异的遗传研究,从1,855个出版物的细节临床表型特征中获得1,288个基因。基于该数据集中的基因型 - 表型相关性,我们开发了一个名为GPCards的用户友好的在线数据库(http://genemed.tech/gpcards/),其不仅提供了遗传疾病和疾病基因之间的关联,而且还提供了普遍存在各种与疾病基因相关的临床表型和这些临床表型和遗传变异之间的患者水平映射。为了加速遗传变异的解释,我们综合了62名众所周知的变异级和基因级基因组数据来源,包括不同群体的功能预测,等位基因频率,以及与疾病相关的信息。此外,GPCards能够自动分析用户自己的遗传数据,综合注释,候选功能变体的优先级,以及使用自定义参数的基因型 - 表型相关性。总之,GPCards预计将加速对人类遗传疾病中基因型 - 表型相关,亚型分类和候选基因优先级的解释。

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