Disclaimer

Oxford University Press makes no representation, express or implied, that the drug dosages in this book are correct. Readers must therefore always check the product information and clinical procedures with the most up to date published product information and data sheets provided by the manufacturers and the most recent codes of conduct and safety regulations. The authors and the publishers do not accept responsibility or legal liability for any errors in the text or for the misuse or misapplication of material in this work. Except where otherwise stated, drug dosages and recommendations are for the non-pregnant adult who is not breastfeeding.

Show Summary Details
Page of

Human Linkage and Association Analysis 

Human Linkage and Association Analysis
Chapter:
Human Linkage and Association Analysis
Author(s):

John P. Rice

DOI:
10.1093/med/9780190221973.003.0005
Page of

PRINTED FROM OXFORD MEDICINE ONLINE (www.oxfordmedicine.com). © Oxford University Press, 2016. All Rights Reserved. Under the terms of the licence agreement, an individual user may print out a PDF of a single chapter of a title in Oxford Medicine Online for personal use (for details see Privacy Policy and Legal Notice).

date: 20 May 2019

The basic idea in linkage analysis is that a disease gene will segregate in a family with a close (linked) marker, and typing this marker will lead to its detection. The successes using this approach have been largely confined to Mendelian monogenic disorders or complex disorders with Mendelian subforms. During the last decade, psychiatric genetics abandoned linkage analysis and moved to case-control studies of association, with remarkable success in identifying susceptibility genes for mental disorders. In this chapter, we review the statistical underpinnings of linkage and association and discuss important issues such as population stratification, imputation, data cleaning, the genomic inflation factor, and QQ and Manhattan plots. The challenge for the next decade will be to understand the biology of these GWAS (genome-wide association study) hits.

Access to the complete content on Oxford Medicine Online requires a subscription or purchase. Public users are able to search the site and view the abstracts for each book and chapter without a subscription.

Please subscribe or login to access full text content.

If you have purchased a print title that contains an access token, please see the token for information about how to register your code.

For questions on access or troubleshooting, please check our FAQs, and if you can't find the answer there, please contact us.