Chapter title |
Analysis of Genome-Wide Association Data.
|
---|---|
Chapter number | 9 |
Book title |
Bioinformatics
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-6613-4_9 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6611-0, 978-1-4939-6613-4
|
Authors |
Allan F. McRae |
Editors |
Jonathan M. Keith |
Abstract |
The last decade has seen substantial advances in the understanding of the genetics of complex traits and disease. This has been largely driven by genome-wide association studies (GWAS), which have identified thousands of genetic loci associated with these traits and disease. This chapter provides a guide on how to perform GWAS on both binary (case-control) and quantitative traits. As poor data quality, through both genotyping failures and unobserved population structure, is a major cause of false-positive genetic associations, there is a particular focus on the crucial steps required to prepare the SNP data prior to analysis. This is followed by the methods used to perform the actual GWAS and visualization of the results. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Australia | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Portugal | 1 | 6% |
Unknown | 15 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 2 | 13% |
Student > Postgraduate | 2 | 13% |
Student > Master | 2 | 13% |
Student > Bachelor | 1 | 6% |
Professor | 1 | 6% |
Other | 3 | 19% |
Unknown | 5 | 31% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 5 | 31% |
Biochemistry, Genetics and Molecular Biology | 3 | 19% |
Social Sciences | 1 | 6% |
Medicine and Dentistry | 1 | 6% |
Unknown | 6 | 38% |