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

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 urgen...

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Autores principales: Li, Bin, Wang, Zheng, Chen, Qian, Li, Kuokuo, Wang, Xiaomeng, Wang, Yijing, Zeng, Qian, Han, Ying, Lu, Bin, Zhao, Yuwen, Zhang, Rui, Jiang, Li, Pan, Hongxu, Luo, Tengfei, Zhang, Yi, Fang, Zhenghuan, Xiao, Xuewen, Zhou, Xun, Wang, Rui, Zhou, Lu, Wang, Yige, Yuan, Zhenhua, Xia, Lu, Guo, Jifeng, Tang, Beisha, Xia, Kun, Zhao, Guihu, Li, Jinchen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8042245/
https://www.ncbi.nlm.nih.gov/pubmed/33868597
http://dx.doi.org/10.1016/j.csbj.2021.03.011
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author Li, Bin
Wang, Zheng
Chen, Qian
Li, Kuokuo
Wang, Xiaomeng
Wang, Yijing
Zeng, Qian
Han, Ying
Lu, Bin
Zhao, Yuwen
Zhang, Rui
Jiang, Li
Pan, Hongxu
Luo, Tengfei
Zhang, Yi
Fang, Zhenghuan
Xiao, Xuewen
Zhou, Xun
Wang, Rui
Zhou, Lu
Wang, Yige
Yuan, Zhenhua
Xia, Lu
Guo, Jifeng
Tang, Beisha
Xia, Kun
Zhao, Guihu
Li, Jinchen
author_facet Li, Bin
Wang, Zheng
Chen, Qian
Li, Kuokuo
Wang, Xiaomeng
Wang, Yijing
Zeng, Qian
Han, Ying
Lu, Bin
Zhao, Yuwen
Zhang, Rui
Jiang, Li
Pan, Hongxu
Luo, Tengfei
Zhang, Yi
Fang, Zhenghuan
Xiao, Xuewen
Zhou, Xun
Wang, Rui
Zhou, Lu
Wang, Yige
Yuan, Zhenhua
Xia, Lu
Guo, Jifeng
Tang, Beisha
Xia, Kun
Zhao, Guihu
Li, Jinchen
author_sort Li, Bin
collection PubMed
description 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.
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spelling pubmed-80422452021-04-16 GPCards: An integrated database of genotype–phenotype correlations in human genetic diseases Li, Bin Wang, Zheng Chen, Qian Li, Kuokuo Wang, Xiaomeng Wang, Yijing Zeng, Qian Han, Ying Lu, Bin Zhao, Yuwen Zhang, Rui Jiang, Li Pan, Hongxu Luo, Tengfei Zhang, Yi Fang, Zhenghuan Xiao, Xuewen Zhou, Xun Wang, Rui Zhou, Lu Wang, Yige Yuan, Zhenhua Xia, Lu Guo, Jifeng Tang, Beisha Xia, Kun Zhao, Guihu Li, Jinchen Comput Struct Biotechnol J Data Article 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. Research Network of Computational and Structural Biotechnology 2021-03-22 /pmc/articles/PMC8042245/ /pubmed/33868597 http://dx.doi.org/10.1016/j.csbj.2021.03.011 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Li, Bin
Wang, Zheng
Chen, Qian
Li, Kuokuo
Wang, Xiaomeng
Wang, Yijing
Zeng, Qian
Han, Ying
Lu, Bin
Zhao, Yuwen
Zhang, Rui
Jiang, Li
Pan, Hongxu
Luo, Tengfei
Zhang, Yi
Fang, Zhenghuan
Xiao, Xuewen
Zhou, Xun
Wang, Rui
Zhou, Lu
Wang, Yige
Yuan, Zhenhua
Xia, Lu
Guo, Jifeng
Tang, Beisha
Xia, Kun
Zhao, Guihu
Li, Jinchen
GPCards: An integrated database of genotype–phenotype correlations in human genetic diseases
title GPCards: An integrated database of genotype–phenotype correlations in human genetic diseases
title_full GPCards: An integrated database of genotype–phenotype correlations in human genetic diseases
title_fullStr GPCards: An integrated database of genotype–phenotype correlations in human genetic diseases
title_full_unstemmed GPCards: An integrated database of genotype–phenotype correlations in human genetic diseases
title_short GPCards: An integrated database of genotype–phenotype correlations in human genetic diseases
title_sort gpcards: an integrated database of genotype–phenotype correlations in human genetic diseases
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8042245/
https://www.ncbi.nlm.nih.gov/pubmed/33868597
http://dx.doi.org/10.1016/j.csbj.2021.03.011
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