In addition to the preanalysis measures such as r2 of MACH and info of IMPUTE, which are the relative information measures only depending on the population allele frequency and imputation accuracy, we proposed an additional post-analysis measure RT2. Our measure is an information measure that assesses the above information but also includes strength of association. When testing independent samples, this is equivalent to the information measure of SNPTEST. For a recessive or dominant model, Marchini et al10 showed that the post-analysis measures are quite different from the preanalysis information measure r2. For strongly associated SNPs under an additive model we showed that RT2 and r2 could be quite different (Figure 2). For example, meta-analyses aim to combine estimates of association parameters, which argues for the use of post-analysis QC measures such as RT2 and SNPTEST info. In situations such as ours, filtering on RT2 leads to a reduction in heterogeneity between studies, making the studies more comparable and meta-analysis more powerful. To interpret the results of meta-analysis properly, it also is important to report the difference between the studies, such as the quality of both genotyping and imputation.
