Strategies for exome and genome sequence data analysis in disease-gene discovery projects
Article first published online: 13 JUN 2011
© 2011 John Wiley & Sons A/S
Special Issue: Exome Sequencing
Volume 80, Issue 2, pages 127–132, August 2011
How to Cite
Robinson, P., Krawitz, P. and Mundlos, S. (2011), Strategies for exome and genome sequence data analysis in disease-gene discovery projects. Clinical Genetics, 80: 127–132. doi: 10.1111/j.1399-0004.2011.01713.x
- Issue published online: 12 JUL 2011
- Article first published online: 13 JUN 2011
- Accepted manuscript online: 26 MAY 2011 10:12AM EST
- Received 9 May 2011, revised and accepted for publication 20 May 2011
- disease gene;
- next-generation sequencing
Robinson PN, Krawitz P, Mundlos S. Strategies for exome and genome sequence data analysis in disease-gene discovery projects.
In whole-exome sequencing (WES), target capture methods are used to enrich the sequences of the coding regions of genes from fragmented total genomic DNA, followed by massively parallel, ‘next-generation’ sequencing of the captured fragments. Since its introduction in 2009, WES has been successfully used in several disease-gene discovery projects, but the analysis of whole-exome sequence data can be challenging. In this overview, we present a summary of the main computational strategies that have been applied to identify novel disease genes in whole-exome data, including intersect filters, the search for de novo mutations, and the application of linkage mapping or inference of identity-by-descent (IBD) in family studies.