Sen Zhao , Xi Cheng , Wen Wen , Guixing Qiu , Terry Jianguo Zhang , Zhihong Wu , Nan Wu
{"title":"Advances in clinical genetics and genomics","authors":"Sen Zhao , Xi Cheng , Wen Wen , Guixing Qiu , Terry Jianguo Zhang , Zhihong Wu , Nan Wu","doi":"10.1016/j.imed.2021.03.005","DOIUrl":null,"url":null,"abstract":"<div><p>Developments in genetics and genomics are progressing at an unprecedented speed. Twenty years ago, the human genome project provided the first glimpses into the human genome sequence and launched a new era of human genetics. The emerging of next-generation sequencing (NGS) in 2005 then made possible comprehensive genetic testing such as exome sequencing and genome sequencing. Meanwhile, great efforts have been put into the optimization of bioinformatic pipelines to make increasingly speedy and accurate variant analyses based on NGS data. These advances in sequencing technologies and analytical methods have revolutionized the diagnostic odyssey of suspected hereditary diseases. More recently, the genotype-phenotype relationship and polygenic risk scores (PRSs) generated from genome-wide association studies have expanded our horizon from rare genetic mutations to a genomic landscape implicated by the combined effect of both rare variants and polymorphisms. At the same time, clinicians and genetic counselors are facing huge challenges conferred by overwhelming genomic knowledge and long sheets of testing reports for comprehensive genomic sequencing. The path toward the “next-generation” clinical genetics and genomics may underlie semiautomatic pipelines assisted by artificial intelligence techniques.</p></div>","PeriodicalId":73400,"journal":{"name":"Intelligent medicine","volume":"1 3","pages":"Pages 128-133"},"PeriodicalIF":4.4000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.imed.2021.03.005","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent medicine","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667102621000176","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 3
Abstract
Developments in genetics and genomics are progressing at an unprecedented speed. Twenty years ago, the human genome project provided the first glimpses into the human genome sequence and launched a new era of human genetics. The emerging of next-generation sequencing (NGS) in 2005 then made possible comprehensive genetic testing such as exome sequencing and genome sequencing. Meanwhile, great efforts have been put into the optimization of bioinformatic pipelines to make increasingly speedy and accurate variant analyses based on NGS data. These advances in sequencing technologies and analytical methods have revolutionized the diagnostic odyssey of suspected hereditary diseases. More recently, the genotype-phenotype relationship and polygenic risk scores (PRSs) generated from genome-wide association studies have expanded our horizon from rare genetic mutations to a genomic landscape implicated by the combined effect of both rare variants and polymorphisms. At the same time, clinicians and genetic counselors are facing huge challenges conferred by overwhelming genomic knowledge and long sheets of testing reports for comprehensive genomic sequencing. The path toward the “next-generation” clinical genetics and genomics may underlie semiautomatic pipelines assisted by artificial intelligence techniques.