Data quality control in genetic case-control association studies.

Journal article

This protocol details the steps for data quality assessment and control that are typically carried out during case-control association studies. The steps described involve the identification and removal of DNA samples and markers that introduce bias. These critical steps are paramount to the success of a case-control study and are necessary before statistically testing for association. We describe how to use PLINK, a tool for handling SNP data, to perform assessments of failure rate per individual and per SNP and to assess the degree of relatedness between individuals. We also detail other quality-control procedures, including the use of SMARTPCA software for the identification of ancestral outliers. These platforms were selected because they are user-friendly, widely used and computationally efficient. Steps needed to detect and establish a disease association using case-control data are not discussed here. Issues concerning study design and marker selection in case-control studies have been discussed in our earlier protocols. This protocol, which is routinely used in our labs, should take approximately 8 h to complete.

Authors: Anderson, C; Pettersson, F; Clarke, G; Cardon, L; Morris, A

• Publication status: Published
• Journal: Nature protocols
• Volume: 5
• Issue: 9
• Pages: 1564-1573
• Publication date: 2010-09-01
• DOI: 10.1038/nprot.2010.116
• EISSN: 1750-2799
• ISSN: 1754-2189
• Language: English
• Keywords: Quality Control; Female; Humans; Genome-Wide Association Study; Genetic Techniques; Computational Biology; Case-Control Studies; Animals; Male