Using the RDP Classifier to Predict Taxonomic Novelty and Reduce the Search Space for Finding Novel Organisms

Abstract

We conclude that selecting a read-length appropriate RDP bootstrap score can significantly reduce the search space for identifying novel genera and higher levels in taxonomy. In addition, having a well-represented database significantly improves performance while having genera that are "highly" similar does not make a significant improvement. On a real dataset from an Amazon Terra Preta soil sample, we show that the detector can predict (or correlates to) whether novel sequences will be assigned to new taxa when the RDP database "doubles" in the future.