Help Login Create account

Data released on July 26, 2016

Supporting data for "Streaming algorithms for identification of pathogens and antibiotic resistance potential from real-time MinIONTM sequencing"

Cao, M, D; Coin, L; Cooper, M, A; Elliott, A, G; Ganesamoorthy, D; Zhang, H (2016): Supporting data for "Streaming algorithms for identification of pathogens and antibiotic resistance potential from real-time MinIONTM sequencing" GigaScience Database. http://dx.doi.org/10.5524/100206 RIS BibTeX Text

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 bene ts such as rapid diagnosis of bacterial infection and identi cation 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 pro le identi cation. 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 minutes of sequencing and using about 500 reads, initial drug-resistance pro les within two hours, and complete resistance pro les within 10 hours. While strain identi cation with multi-locus sequence typing required more than 15x coverage to generate con dent assignments, our novel gene-presence typing could detect the presence of a known strain with 0.5x coverage. We also show that our pipeline can process over 100 times more data than the current throughput of the MinION on a desktop computer.

Contact Submitter

Related manuscripts:

doi:10.1186/s13742-016-0137-2

Additional information:

https://github.com/mdcao/npAnalysis

https://github.com/mdcao/japsa

Accessions (data included in GigaDB):

BioProject: PRJEB14532

Keywords:

Nanopore sequencing Real-time analysis Pathogen identi cation Antibiotic resistance 

Software, Genomic

/images/uploads/image_upload/Images_276.png

Samples: Table Settings

Columns:

Common Name
Scienfic Name
Sample Attributes
Taxonomic ID
Genbank Name

Sample IDTaxonomic IDCommon NameGenbank NameScientific NameSample Attributes
Klebsiella pneumoniae ATCC-13883573  Klebsiella pneumoniae Isolation source:human urine
Strain:ATCC-13883
Serovar:NCTC 9633, NCDC 298-53, NCDC 410-68
...
+
Klebsiella pneumoniae ATCC-7006031276653Klebsiella pneumoniae ATCC-700603 Isolation source:human urine
Strain:ATCC-700603
Serovar:1000527, 7561
...
+
Klebsiella pneumoniae BAA-21461263871Klebsiella pneumoniae BAA-2146 Isolation source:human urine
Strain:ATCC BAA-2146
Serovar:K6, CCUG 45421, LMG 20218, MCV37
...
+
Displaying 1-3 of 3 Sample(s).

Files: (FTP site) Table Settings

Columns:

File Description
Sample ID
File Type
File Format
Size
Release Date
Download Link
File Attributes

File NameSample IDFile TypeFile FormatSizeRelease Date 
archivearchive4.5 KB2016-07-01
archiveTAR2.3 MB2016-07-01
archiveTAR82.3 MB2016-07-01
archiveTAR207 KB2016-07-01
archiveTAR2.7 GB2016-07-01
archivearchive400 KB2016-07-01
archiveTAR6.7 GB2016-07-01
archiveTAR282 MB2016-07-01
MD5sumTEXT0.68 KB2016-07-01
ReadmeTEXT1.3 KB2016-07-01
Displaying 1-10 of 10 File(s).

History:

+

Other datasets you might like: