CHANGES IN VERSION 1.6.0
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    o New function `evalTypeIError` for type I error rate evalution by sample permutation:
      - evaluation of one or more enrichment methods on one or more expression datasets
      - support for splitting permutations into blocks of defined size, and invoking 
        parallel evaluation of the partitions 
    o New function `evalRandomGS` for evaluation of random gene sets:
      - estimates proportion of rejected null hypotheses (= fraction of significant 
        gene sets) of an enrichment method when applied to random gene sets of defined size
      - evaluation of one or more enrichment methods on an expression dataset of choice
    o New argument `method` to the `evalRelevance` function for the evaluation
      of phenotype relevance of gene set rankings, choices include:
      - "wsum": computes a weighted sum of the relevance scores (default),
      - "auc": performs a ROC/AUC analysis based on the ROCR package,
      - "cor": computes a standard correlation measure such as Spearman's rank correlation,
      - a user-defined function for customized behaviors.
    o New function `metaFC` for summarizing fold changes of individual datasets 
      across a compendium of expression datasets
    o New functions `plotDEDistribution` and `plotNrSamples` for exploring 
      differential expression and sample size across a compendium of expression datasets
    o Extended support for user-defined benchmarking inputs including simplified 
      plug-in of user-defined enrichment methods (thanks to Marcel Ramos @LiNk-NY)