Faculty Opinions recommendation of Enhancing linkage analysis of complex disorders: an evaluation of high-density genotyping.

Author(s):  
Carol Mathews
2018 ◽  
pp. 70-83
Author(s):  
John P. Rice

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.


2007 ◽  
Vol 24 (1) ◽  
pp. 86-93 ◽  
Author(s):  
Guohui Lin ◽  
Zhanyong Wang ◽  
Lusheng Wang ◽  
Yu-Lung Lau ◽  
Wanling Yang

2017 ◽  
Author(s):  
Peter M. Bourke ◽  
Geert van Geest ◽  
Roeland E. Voorrips ◽  
Johannes Jansen ◽  
Twan Kranenburg ◽  
...  

AbstractMotivationPolyploid species carry more than two copies of each chromosome, a condition found in many of the world’s most important crops. Genetic mapping in polyploids is more complex than in diploid species, resulting in a lack of available software tools. These are needed if we are to realise all the opportunities offered by modern genotyping platforms for genetic research and breeding in polyploid crops.ResultspolymapR is an R package for genetic linkage analysis and integrated genetic map construction from bi-parental populations of outcrossing autopolyploids. It can currently analyse triploid, tetraploid and hexaploid marker datasets and is applicable to various crops including potato, leek, alfalfa, blueberry, chrysanthemum, sweet potato or kiwifruit. It can detect, estimate and correct for preferential chromosome pairing, and has been tested on high-density marker datasets from potato, rose and chrysanthemum, generating high-density integrated linkage maps in all of these crops.Availability and ImplementationpolymapR is freely available under the general public license from the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org/packages=polymapR.ContactChris Maliepaard [email protected] or Roeland E. Voorrips [email protected]


2005 ◽  
Vol 77 (6) ◽  
pp. 937-944 ◽  
Author(s):  
Tadao Arinami ◽  
Tsuyuka Ohtsuki ◽  
Hiroki Ishiguro ◽  
Hiroshi Ujike ◽  
Yuji Tanaka ◽  
...  

2008 ◽  
Vol 13 (5) ◽  
pp. 522-530 ◽  
Author(s):  
M Romanos ◽  
C Freitag ◽  
C Jacob ◽  
D W Craig ◽  
A Dempfle ◽  
...  

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