programfiles/nanoraw

Genome guided re-segmention and visualization for raw nanopore sequencing data.

Summary

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

Installation

Install nanoraw via pip

pip install nanoraw

Install bleeding edge via github

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

Usage

nanoraw -h
nanoraw [command] [options]

Main Comand (Must be run before any other commands):

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

Genome Anchored Plotting Commands:

 plot_max_coverage             Plot signal in regions with the maximum coverage.
 plot_genome_location          Plot signal at defined genomic locations.
 plot_kmer_centered            Plot signal at regions centered on a specific kmer.
 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_kmer_with_stats          Plot signal from several regions and test statistics centered on a k-mer of interst.

Sequencing Time Anchored Plotting Commands:

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

Other Plotting Commands:

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

Auxiliary Commands:

 write_most_significant        Write sequence where signal differs the most significantly between two groups.
 write_wiggle                  Write wiggle file of genome coverage from genome_resquiggle mappings.

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

Requirements

• HDF5 (http://micro.stanford.edu/wiki/Install_HDF5#Install)
• graphmap (https://github.com/isovic/graphmap)

python Requirements (handled by pip):

• numpy
• scipy
• h5py
• rpy2 (along with an R installation)

Optional python Requirements:

• Biopython (for robust FASTA parsing, but a simple parser is provided)

Optional R Requirements (install with install.packages([package_name]) from an R prompt):

• changepoint (for using R's changepoint package for re-segmentation)
• ggplot2 (required for any plotting subcommands)
• cowplot (required for plot_kmer_with_stats subcommand)

Legal

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 [email protected] 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.