Identifying highly-penetrant disease causal mutations using next generation sequencing: Guide to whole process

A. Mesut Erzurumluoglu, Santiago Rodriguez, Ian N M Day, Tom R Gaunt, Tom G Richardson, Hashem A Shihab, Denis A Baird

Research output: Contribution to journalReview article (Academic Journal)peer-review

6 Citations (Scopus)


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, 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 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 non-consanguineous; and when Mendelian disorders are analysed as opposed to common-complex disorders.
Original languageEnglish
Article number923491
JournalBioMed Research International
Publication statusPublished - 1 Apr 2015


  • Next generation sequencing
  • Variant effect predictor
  • Autozygosity mapping
  • Bioinformatics
  • Genetics
  • Consanguinity
  • Mutation analysis
  • whole-exome sequencing


Dive into the research topics of 'Identifying highly-penetrant disease causal mutations using next generation sequencing: Guide to whole process'. Together they form a unique fingerprint.

Cite this