This package provides tools for the analysis of raw nanopore sequencing data, including correction of basecalls and visualization.

Full documentation available at Read the Docs

Install nanoraw without plotting dependencies (base genome_resquiggle algorithm and text outputs: wig and fasta)

pip install nanoraw

Install nanoraw with plotting dependencies (requires separate installation of R packages ggplot2 and cowplot)

pip install nanoraw[plot]

Install bleeding edge via github

pip install git+https://github.com/marcus1487/nanoraw.git

nanoraw -h
nanoraw [command] [options]

 genome_resquiggle             Re-annotate raw signal with genomic aignement of existing basecalls.

 plot_max_coverage             Plot signal in regions with the maximum coverage.
 plot_genome_location          Plot signal at defined genomic locations.
 plot_motif_centered           Plot signal at regions centered on a specific motif.
 plot_max_difference           Plot signal where signal differs the most between two groups.
 plot_most_significant         Plot signal where signal differs the most significantly between two groups.
 plot_motif_with_stats         Plot signal from several regions and test statistics centered on a motif of interst.

 plot_correction               Plot segmentation before and after correction.
 plot_multi_correction         Plot multiple raw signals anchored by genomic location.

 cluster_most_significant      Clustering traces at bases with significant differences.
 plot_kmer                     Plot signal quantiles acorss kmers.

 write_most_significant        Write sequence where signal differs the most significantly between two groups.
 write_wiggles                 Write wiggle files for nanopore signal values, coverage, and statistics.

Get additional help for subcommands with nanoraw [command] -h

• HDF5 (http://micro.stanford.edu/wiki/Install_HDF5#Install)
• graphmap (https://github.com/isovic/graphmap) OR
• BWA-MEM (http://bio-bwa.sourceforge.net/)

• numpy
• scipy
• h5py

• rpy2 (along with an R installation)
• ggplot2 (required for any plotting subcommands)
• cowplot (required for plot_motif_with_stats subcommand)

Stoiber, M.H. et al. De novo Identification of DNA Modifications Enabled by Genome-Guided Nanopore Signal Processing. bioRxiv (2016).

http://biorxiv.org/content/early/2017/04/10/094672

nanoraw v.1 Copyright (c) 2016, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.

If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Innovation and Partnerships department at IPO@lbl.gov referring to " nanoraw v.1 (2016-199)."

NOTICE. This software was developed under funding from the U.S. Department of Energy. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, prepare derivative works, and perform publicly and display publicly. Beginning five (5) years after the date permission to assert copyright is obtained from the U.S. Department of Energy, and subject to any subsequent five (5) year renewals, the U.S. Government is granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, prepare derivative works, distribute copies to the public, perform publicly and display publicly, and to permit others to do so.