You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
| Chapter title |
An Overview of Genome-Wide Association Studies
|
|---|---|
| Chapter number | 6 |
| Book title |
Computational Systems Biology
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7717-8_6 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7716-1, 978-1-4939-7717-8
|
| Authors |
Michelle Chang, Lin He, Lei Cai |
| Abstract |
Genome-wide association study (GWAS) is a powerful study design to identify genetic variants of a trait and, in particular, detect the association between common single-nucleotide polymorphisms (SNPs) and common human diseases such as heart disease, inflammatory bowel disease, type 2 diabetes, and psychiatric disorders. The standard strategy of population-based case-control studies for GWAS is illustrated in this chapter. We provide an overview of the concepts underlying GWAS, as well as provide guidelines for statistical methods performed in GWAS. |
Mendeley readers
The data shown below were compiled from readership statistics for 126 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 126 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 21 | 17% |
| Student > Ph. D. Student | 18 | 14% |
| Student > Bachelor | 11 | 9% |
| Student > Doctoral Student | 9 | 7% |
| Researcher | 8 | 6% |
| Other | 9 | 7% |
| Unknown | 50 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 27 | 21% |
| Agricultural and Biological Sciences | 18 | 14% |
| Medicine and Dentistry | 5 | 4% |
| Neuroscience | 4 | 3% |
| Engineering | 4 | 3% |
| Other | 14 | 11% |
| Unknown | 54 | 43% |