We have met with some success in the current version but want to have increased automated discrimination. We have a well-defined path to completing this aim. The use of properly designed resequencing microarrays and this automated detection algorithm provides a way forward to developing assays that can test for multiple organisms simultaneously while providing fine strain level discrimination giving access to information about detailed strain recognition, antibiotic resistance markers and pathogenicity. This is a capability that other approaches cannot currently provide. In addition, since the design of the original 30 kb RPM microarray, the possible sequence content of the current array has increased 10-fold to 300 kb and further increases in array density are still attainable. This, coupled with our identification algorithms, will allow the analysis of partial sequence information from even more organisms for applications such as differential diagnostics for illnesses with multiple potential causes (i.e. febrile respiratory illness), tracking of emergent pathogens, distinction of biological threats from harmless near genetic neighbors in surveillance applications and for tracking the impact of coinfections or super infections. The concept of categorizing and reporting different degrees of identification depending on the quality of samples and set of target sequences is not limited to resequencing microarrays but is more generally applicable to any platform that is capable of returning sequence level calls that can be used to query a reference DNA database. As the trend for assays that test for multiple pathogens increases, automated analysis tools, such as this one, become more crucial for rapid identification in simple formats useful to the non-expert on a day to day basis. The remaining hurdle to using resequencing microarrays as a routine assay method is now clearly the sample processing methods. Further automating these steps is an important area of future research and development.