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Poretools: a toolkit for analyzing nanopore sequence data.

Loman NJ, Quinlan AR - Bioinformatics (2014)

Bottom Line: Currently, the research community lacks a standardized toolkit for the analysis of nanopore datasets.Poretools operates directly on the native FAST5 (an application of the HDF5 standard) file format produced by ONT and provides a wealth of format conversion utilities and data exploration and visualization tools.Poretools is an open-source software and is written in Python as both a suite of command line utilities and a Python application programming interface.

View Article: PubMed Central - PubMed

Affiliation: Institute of Microbiology and Infection, University of Birmingham, Birmingham B15 2TT, UK and Department of Public Health Sciences, University of Virginia, Charlottesville 22932, VA, USA.

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Example poretools visualizations from a set of FAST5 files generated by a single MinION™ run. Panel A shows a histogram of read lengths. Panel B shows a collector’s curve of reads over time. Panel C shows an example squiggle plot of detected event transitions originating from MinION™
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btu555-F1: Example poretools visualizations from a set of FAST5 files generated by a single MinION™ run. Panel A shows a histogram of read lengths. Panel B shows a collector’s curve of reads over time. Panel C shows an example squiggle plot of detected event transitions originating from MinION™

Mentions: There is a need to visualize MinION™ run performance to assess its quality and troubleshoot different fragmentation and library preparation strategies. Poretools provides two utilties, hist and yield_plot, that characterize the fragment size distribution and display a collector’s curve of the overall sequencing yield, respectively. Example commands are provided here, with corresponding figures shown (Fig. 1A and B).


Poretools: a toolkit for analyzing nanopore sequence data.

Loman NJ, Quinlan AR - Bioinformatics (2014)

Example poretools visualizations from a set of FAST5 files generated by a single MinION™ run. Panel A shows a histogram of read lengths. Panel B shows a collector’s curve of reads over time. Panel C shows an example squiggle plot of detected event transitions originating from MinION™
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4296151&req=5

btu555-F1: Example poretools visualizations from a set of FAST5 files generated by a single MinION™ run. Panel A shows a histogram of read lengths. Panel B shows a collector’s curve of reads over time. Panel C shows an example squiggle plot of detected event transitions originating from MinION™
Mentions: There is a need to visualize MinION™ run performance to assess its quality and troubleshoot different fragmentation and library preparation strategies. Poretools provides two utilties, hist and yield_plot, that characterize the fragment size distribution and display a collector’s curve of the overall sequencing yield, respectively. Example commands are provided here, with corresponding figures shown (Fig. 1A and B).

Bottom Line: Currently, the research community lacks a standardized toolkit for the analysis of nanopore datasets.Poretools operates directly on the native FAST5 (an application of the HDF5 standard) file format produced by ONT and provides a wealth of format conversion utilities and data exploration and visualization tools.Poretools is an open-source software and is written in Python as both a suite of command line utilities and a Python application programming interface.

View Article: PubMed Central - PubMed

Affiliation: Institute of Microbiology and Infection, University of Birmingham, Birmingham B15 2TT, UK and Department of Public Health Sciences, University of Virginia, Charlottesville 22932, VA, USA.

Show MeSH