Streaming algorithms for identification of pathogens and antibiotic resistance potential from real-time MinION(TM) sequencing.

ABSTRACT: The recently introduced Oxford Nanopore MinION platform generates DNA sequence data in real-time. This has great potential to shorten the sample-to-results time and is likely to have benefits such as rapid diagnosis of bacterial infection and identification of drug resistance. However, there are few tools available for streaming analysis of real-time sequencing data. Here, we present a framework for streaming analysis of MinION real-time sequence data, together with probabilistic streaming algorithms for species typing, strain typing and antibiotic resistance profile identification. Using four culture isolate samples, as well as a mixed-species sample, we demonstrate that bacterial species and strain information can be obtained within 30 min of sequencing and using about 500 reads, initial

SUBMITTER: Cao MD 

PROVIDER: S-EPMC4960868 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature