There are a number of ways in which DetectiV may be developed. In terms of visualization, better browsing capabilities of the barplots would be desirable, perhaps using a web-interface. In terms of the analysis, we may borrow ideas from gene expression arrays. For example, limma uses an empirical Bayes method to shrink each gene's standard error towards a common value, and has been shown to perform better than standard statistical methods [12] . It may be that we can apply a similar method here to shrink the standard error for each virus species towards a common value, thus increasing sensitivity. It may also be possible to apply multiple-testing procedures to the resulting p values. The Bonferroni correction may be appropriate, in which the p values are multiplied by the number of comparisons, or a more conservative approach may be needed, such as that suggested by Benjamini and Hochberg [19] , in order to control the false discovery rate.