diseaseGPS: auxiliary diagnostic system for genetic disorders based on genotype and phenotype.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
02 09 2023
Historique:
received: 05 03 2023
revised: 24 07 2023
medline: 15 9 2023
pubmed: 30 8 2023
entrez: 30 8 2023
Statut: ppublish

Résumé

The next-generation sequencing brought opportunities for the diagnosis of genetic disorders due to its high-throughput capabilities. However, the majority of existing methods were limited to only sequencing candidate variants, and the process of linking these variants to a diagnosis of genetic disorders still required medical professionals to consult databases. Therefore, we introduce diseaseGPS, an integrated platform for the diagnosis of genetic disorders that combines both phenotype and genotype data for analysis. It offers not only a user-friendly GUI web application for those without a programming background but also scripts that can be executed in batch mode for bioinformatics professionals. The genetic and phenotypic data are integrated using the ACMG-Bayes method and a novel phenotypic similarity method, to prioritize the results of genetic disorders. diseaseGPS was evaluated on 6085 cases from Deciphering Developmental Disorders project and 187 cases from Shanghai Children's hospital. The results demonstrated that diseaseGPS performed better than other commonly used methods. diseaseGPS is available to freely accessed at https://diseasegps.sjtu.edu.cn with source code at https://github.com/BioHuangDY/diseaseGPS.

Identifiants

pubmed: 37647638
pii: 7255909
doi: 10.1093/bioinformatics/btad517
pmc: PMC10500091
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2023. Published by Oxford University Press.

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Auteurs

Daoyi Huang (D)

State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
SJTU-Yale Joint Center for Biostatistics and Data Science, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China.

Jianping Jiang (J)

State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
SJTU-Yale Joint Center for Biostatistics and Data Science, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China.
Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

Tingting Zhao (T)

Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Shanghai Engineering Research Center for Big Data in Pediatric Precision Medicine, Shanghai, China.

Shengnan Wu (S)

Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

Pin Li (P)

Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

Yongfen Lyu (Y)

Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

Jincai Feng (J)

Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

Mingyue Wei (M)

Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

Zhixing Zhu (Z)

Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Shanghai Engineering Research Center for Big Data in Pediatric Precision Medicine, Shanghai, China.

Jianlei Gu (J)

State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
SJTU-Yale Joint Center for Biostatistics and Data Science, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China.

Yongyong Ren (Y)

State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
SJTU-Yale Joint Center for Biostatistics and Data Science, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China.

Guangjun Yu (G)

Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Shanghai Engineering Research Center for Big Data in Pediatric Precision Medicine, Shanghai, China.
School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China.

Hui Lu (H)

State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
SJTU-Yale Joint Center for Biostatistics and Data Science, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China.
Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

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