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Automated quality control for genome wide association studies
This paper provides details on the necessary steps to assess and control data in genome wide association studies (GWAS) using genotype information on a large number of genetic markers for large number of individuals. Due to varied study designs and genotyping platforms between multiple sites/project...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
F1000Research
2016
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5007749/ https://www.ncbi.nlm.nih.gov/pubmed/27635224 http://dx.doi.org/10.12688/f1000research.9271.1 |
| Sumario: | This paper provides details on the necessary steps to assess and control data in genome wide association studies (GWAS) using genotype information on a large number of genetic markers for large number of individuals. Due to varied study designs and genotyping platforms between multiple sites/projects as well as potential genotyping errors, it is important to ensure high quality data. Scripts and directions are provided to facilitate others in this process. |
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