Function to fit the meta-analytic fixed- and random-effects models.The data consists of effect sizes and corresponding variances from your own method/calculations.
● Data Source:
CranContrib
● Keywords: FEM, REM
● Alias: MetaDE.ES
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MetaDE MetaDE package implements 12 major meta-analysis methods for differential expression analysis : Fisher (Rhodes, et al., 2002), Stouffer (Stouffer, 1949), adaptively weighted Fisher (AW) (Li and Tseng, 2011), minimum p-value (minP), maximum p-value (maxP), rth ordered p-value (rOP) (Song and Tseng, 2012), fixed effects model (FEM), random effects model (REM) (Choi, et al., 2003), rank product (rankProd) (Hong, et al., 2006), naive sum of ranks and naive product of ranks (Dreyfuss, et al., 2009). Detailed algorithms, pros and cons of different methods have been discussed in a recent review paper (Tseng, et al., 2012). In addition to selecting a meta-analysis method, two additional considerations are involved in the implementation: (1) Choice of test statistics: Different test statistics are available in the package for each type of outcome variable (e.g. t-statistic or moderated t-statistic for binary outcome, F-statistic for multi-class outcome, regression or correlation for continuous outcome and Cox proportional hazard model for survival outcome). Additionally, a minimum multi-class correlation (min-MCC) has been included for multi-class outcome to only capture concordant expression patterns that F-statistic often fails (Lu, et al., 2010); (2) One-sided test correction: When combining two-sided p-values for binary outcomes, DE genes with discordant DE direction may be identified and the results are difficult to interpret(e.g. up-regulation in one study but down-regulation in another study). One-sided test correction is helpful to guarantee identification of DE genes with concordant DE direction. For example, Pearson's correction has been proposed for Fisher's method (Owen, 2009). In addition to the choices above, MetaDE also provides options for gene matching across studies and gene filtering before meta-analysis. Outputs of the meta-analysis results include DE gene lists with corresponding raw p-value, q-values and various visualization tools. Heatmaps can be plotted across studies.
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