specificity control for read alignments using an artificial reference

 ARDEN (Artificial Reference Driven Estimation of false positives in NGS
 data) is a novel benchmark that estimates error rates based on real
 experimental reads and an additionally generated artificial reference
 genome. It allows the computation of error rates specifically for a
 dataset and the construction of a ROC-curve. Thereby, it can be used to
 optimize parameters for read mappers, to select read mappers for a
 specific problem or also to filter alignments based on quality
 estimation.