title: Identifying Highly Penetrant Disease Causal Mutations Using Next Generation Sequencing: Guide to Whole Process.
abstract: Recent technological advances have created challenges for geneticists and a need to adapt to a wide range of new bioinformatics tools and an expanding wealth of publicly available data (e.g., mutation databases, and software). This wide range of methods and a diversity of file formats used in sequence analysis is a significant issue, with a considerable amount of time spent before anyone can even attempt to analyse the genetic basis of human disorders. Another point to consider that is although many possess "just enough" knowledge to analyse their data, they do not make full use of the tools and databases that are available and also do not fully understand how their data was created. The primary aim of this review is to document some of the key approaches and provide an analysis schema to make the analysis process more efficient and reliable in the context of discovering highly penetrant causal mutations/genes. This review will also compare the methods used to identify highly penetrant variants when data is obtained from consanguineous individuals as opposed to nonconsanguineous; and when Mendelian disorders are analysed as opposed to common-complex disorders.
authors.affiliation: Bristol Genetic Epidemiology Laboratories (BGEL), School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
authors.forename: A Mesut
authors.initials: AM
authors.lastname: Erzurumluoglu
authors.affiliation: Bristol Genetic Epidemiology Laboratories (BGEL), School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
authors.forename: Santiago
authors.identifier: 0000-0001-6551-932X
authors.initials: S
authors.lastname: Rodriguez
authors.affiliation: MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
authors.forename: Hashem A
authors.initials: HA
authors.lastname: Shihab
authors.affiliation: Bristol Genetic Epidemiology Laboratories (BGEL), School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
authors.forename: Denis
authors.initials: D
authors.lastname: Baird
authors.affiliation: Bristol Genetic Epidemiology Laboratories (BGEL), School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK ; MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
authors.forename: Tom G
authors.initials: TG
authors.lastname: Richardson
authors.affiliation: Bristol Genetic Epidemiology Laboratories (BGEL), School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
authors.forename: Ian N M
authors.initials: IN
authors.lastname: Day
authors.affiliation: Bristol Genetic Epidemiology Laboratories (BGEL), School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK ; MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
authors.forename: Tom R
authors.initials: TR
authors.lastname: Gaunt
mesh_terms: D030541:Databases, Genetic; D059472:Exome / Q000235:genetics*; D030342:Genetic Diseases, Inborn / Q000175:diagnosis / Q000235:genetics*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D009154:Mutation; D012984:Software