Abstract
This article presents a new algorithm for finding oligonucleotide signatures that are specific and sensitive for organisms or groups of organisms in large-scale sequence datasets. We assume that the organisms have been organized in a hierarchy, for example, a phylogenetic tree. The resulting signatures, binding sites for primers and probes, match the maximum possible number of organisms in the target group while having at most k matches outside of the target group. The key step in the algorithm is the use of the lowest common ancestor (LCA) to search the organism hierarchy; this allows the combinatorial problem in almost linear time (empirically observed) to be solved. The presented algorithm improves performance by several orders of magnitude in terms of both memory consumption and runtime when compared to the best-known previous algorithms while giving identical, exact solutions. This article gives a formal description of the algorithm, discusses details of our concrete, publicly available implementation, and presents the results from our performance evaluation.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.