Presented at London Calling 2016
Created on 9th December 2015
This paper has been published in GigaScience.
Note: this is an old submission, see here for the current submission.
The recently introduced Oxford Nanopore MinION platform generates DNA sequence data in real-time. This opens immense potential to shorten the sample-to-results time and is likely to lead to enormous benefits in rapid diagnosis of bacterial infection and identification of drug resistance. However, there are very 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 three culture isolate samples as well as a mixed sample, we demonstrate that bacterial species and strain information can be obtained within 30 minutes of sequencing and using about 500 reads, initial drug-resistance profiles within two hours, and complete resistance profiles within 10 hours. We also show that our pipeline can process over 100 times more data than the current throughput of the MinION on a desktop computer.Show more
|Willem Van Schaik||Completed||18 Jan 2016||View review and response|
|Mick Watson||Completed||10 Feb 2016||View review and response|
|Willem Van Schaik||Completed||18 Jan 2016||View review|
|Mick Watson||Completed||10 Feb 2016||View review|
|Willem Van Schaik||Completed||10 May 2016||View review|
|Mick Watson||Completed||10 May 2016||View review|