A Review of Study Designs and Statistical Methods for Genomic Epidemiology Studies using Next Generation Sequencing
Results from numerous linkage and association studies have greatly deepened scientists’ understanding of the genetic basis of many human diseases, yet some important questions remain unanswered. For example, although a large number of disease-associated loci have been identified from genome-wide ass...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2015-04-01
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| Series: | Frontiers in Genetics |
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| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fgene.2015.00149/full |
| _version_ | 1818541169387241472 |
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| author | Qian eWang Qiongshi eLu Hongyu eZhao Hongyu eZhao Hongyu eZhao |
| author_facet | Qian eWang Qiongshi eLu Hongyu eZhao Hongyu eZhao Hongyu eZhao |
| author_sort | Qian eWang |
| collection | DOAJ |
| description | Results from numerous linkage and association studies have greatly deepened scientists’ understanding of the genetic basis of many human diseases, yet some important questions remain unanswered. For example, although a large number of disease-associated loci have been identified from genome-wide association studies (GWAS) in the past 10 years, it is challenging to interpret these results as most disease-associated markers have no clear functional roles in disease etiology, and all the identified genomic factors only explain a small portion of disease heritability. With the help of next-generation sequencing (NGS), diverse types of genomic and epigenetic variations can be detected with high accuracy. More importantly, instead of using linkage disequilibrium to detect association signals based on a set of pre-set probes, NGS allows researchers to directly study all the variants in each individual, therefore promises opportunities for identifying functional variants and a more comprehensive dissection of disease heritability. Although the current scale of NGS studies is still limited due to the high cost, the success of several recent studies suggests the great potential for applying NGS in genomic epidemiology, especially as the cost of sequencing continues to drop. In this review, we discuss several pioneer applications of NGS, summarize scientific discoveries for rare and complex diseases, and compare various study designs including targeted sequencing and whole-genome sequencing using population-based and family-based cohorts. Finally, we highlight recent advancements in statistical methods proposed for sequencing analysis, including group-based association tests, meta-analysis techniques, and annotation tools for variant prioritization. |
| first_indexed | 2024-12-11T22:05:03Z |
| format | Article |
| id | doaj.art-376caad912cf4cafa4adeeee09d6a259 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-11T22:05:03Z |
| publishDate | 2015-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-376caad912cf4cafa4adeeee09d6a2592022-12-22T00:48:58ZengFrontiers Media S.A.Frontiers in Genetics1664-80212015-04-01610.3389/fgene.2015.00149135502A Review of Study Designs and Statistical Methods for Genomic Epidemiology Studies using Next Generation SequencingQian eWang0Qiongshi eLu1Hongyu eZhao2Hongyu eZhao3Hongyu eZhao4Yale UniversityYale UniversityYale UniversityYale UniversityVA Cooperative Studies Program Coordinating CenterResults from numerous linkage and association studies have greatly deepened scientists’ understanding of the genetic basis of many human diseases, yet some important questions remain unanswered. For example, although a large number of disease-associated loci have been identified from genome-wide association studies (GWAS) in the past 10 years, it is challenging to interpret these results as most disease-associated markers have no clear functional roles in disease etiology, and all the identified genomic factors only explain a small portion of disease heritability. With the help of next-generation sequencing (NGS), diverse types of genomic and epigenetic variations can be detected with high accuracy. More importantly, instead of using linkage disequilibrium to detect association signals based on a set of pre-set probes, NGS allows researchers to directly study all the variants in each individual, therefore promises opportunities for identifying functional variants and a more comprehensive dissection of disease heritability. Although the current scale of NGS studies is still limited due to the high cost, the success of several recent studies suggests the great potential for applying NGS in genomic epidemiology, especially as the cost of sequencing continues to drop. In this review, we discuss several pioneer applications of NGS, summarize scientific discoveries for rare and complex diseases, and compare various study designs including targeted sequencing and whole-genome sequencing using population-based and family-based cohorts. Finally, we highlight recent advancements in statistical methods proposed for sequencing analysis, including group-based association tests, meta-analysis techniques, and annotation tools for variant prioritization.http://journal.frontiersin.org/Journal/10.3389/fgene.2015.00149/fullNext-generation sequencingstatistical methodsStudy DesignGenomic epidemiologyGenetic etiology |
| spellingShingle | Qian eWang Qiongshi eLu Hongyu eZhao Hongyu eZhao Hongyu eZhao A Review of Study Designs and Statistical Methods for Genomic Epidemiology Studies using Next Generation Sequencing Frontiers in Genetics Next-generation sequencing statistical methods Study Design Genomic epidemiology Genetic etiology |
| title | A Review of Study Designs and Statistical Methods for Genomic Epidemiology Studies using Next Generation Sequencing |
| title_full | A Review of Study Designs and Statistical Methods for Genomic Epidemiology Studies using Next Generation Sequencing |
| title_fullStr | A Review of Study Designs and Statistical Methods for Genomic Epidemiology Studies using Next Generation Sequencing |
| title_full_unstemmed | A Review of Study Designs and Statistical Methods for Genomic Epidemiology Studies using Next Generation Sequencing |
| title_short | A Review of Study Designs and Statistical Methods for Genomic Epidemiology Studies using Next Generation Sequencing |
| title_sort | review of study designs and statistical methods for genomic epidemiology studies using next generation sequencing |
| topic | Next-generation sequencing statistical methods Study Design Genomic epidemiology Genetic etiology |
| url | http://journal.frontiersin.org/Journal/10.3389/fgene.2015.00149/full |
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