| Title |
From sexless to sexy: Why it is time for human genetics to consider and report analyses of sex
|
|---|---|
| Published in |
Biology of Sex Differences, May 2017
|
| DOI | 10.1186/s13293-017-0136-8 |
| Pubmed ID | |
| Authors |
Matthew S. Powers, Phillip H. Smith, Sherry A. McKee, Marissa A. Ehringer |
| Abstract |
Science has come a long way with regard to the consideration of sex differences in clinical and preclinical research, but one field remains behind the curve: human statistical genetics. The goal of this commentary is to raise awareness and discussion about how to best consider and evaluate possible sex effects in the context of large-scale human genetic studies. Over the course of this commentary, we reinforce the importance of interpreting genetic results in the context of biological sex, establish evidence that sex differences are not being considered in human statistical genetics, and discuss how best to conduct and report such analyses. Our recommendation is to run stratified analyses by sex no matter the sample size or the result and report the findings. Summary statistics from stratified analyses are helpful for meta-analyses, and patterns of sex-dependent associations may be hidden in a combined dataset. In the age of declining sequencing costs, large consortia efforts, and a number of useful control samples, it is now time for the field of human genetics to appropriately include sex in the design, analysis, and reporting of results. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 50% |
| Netherlands | 1 | 17% |
| Sweden | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 2 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 19% |
| Student > Master | 5 | 19% |
| Researcher | 5 | 19% |
| Student > Bachelor | 3 | 11% |
| Other | 2 | 7% |
| Other | 4 | 15% |
| Unknown | 3 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 26% |
| Biochemistry, Genetics and Molecular Biology | 5 | 19% |
| Agricultural and Biological Sciences | 5 | 19% |
| Neuroscience | 2 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 4% |
| Other | 3 | 11% |
| Unknown | 4 | 15% |