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aakbar -- amino-acid k-mer signature tools

Project description

Amino-Acid k-mer tools for creating, searching, and analyzing phylogenetic signatures from genomes or reads of DNA.

Prerequisites

A 64-bit Python 3.4 or greater is required. 8 GB or more of memory is recommended.

The python dependencies of aakbar are: biopython, click>=5.0, click_plugins numpy, pandas, pyfaidx, and pyyaml. Running the examples also requires the pyfastaq https://pypi.python.org/pypi/pyfastaq package.

If you don’t have a python installed that meets these requirements, I recommend getting Anaconda Python <https://www.continuum.io/downloads> on MacOSX and Windows for the smoothness of installation and for the packages that come pre-installed. Once Anaconda python is installed, you can get the dependencies like this on MacOSX:

export PATH=~/anaconda/bin:${PATH}    # you might want to put this in your .profile
conda install click
conda install --channel https://conda.anaconda.org/IOOS click-plugins
conda install --channel https://conda.anaconda.org/bioconda pyfaidx
conda install --channel https://conda.anaconda.org/bioconda pyfastaq

Installation

This package is tested under Linux and MacOS using Python 3.5 and is available from the PyPI. To install via pip (or pip3 under some distributions) :

pip install aakbar

If you wish to develop aakbar, download a release and in the top-level directory:

pip install --editable .

If you wish to have pip install directly from git, use this command:

pip install git+https://github.com/ncgr/aakbar.git

Usage

Installation puts a single script called aakbar in your path. The usage format is:

aakbar [GLOBALOPTIONS] COMMAND [COMMANDOPTIONS] [ARGS]

A listing of commands is available via aakbar --help. Current available commands are:

calculate-peptide-terms

Write peptide terms and histograms.

conserved-signature-stats

Stats on signatures found in all input genomes.

define-set

Define an identifier and directory for a set.

define-summary

Define summary directory and label.

demo-simplicity

Demo self-provided simplicity outputs.

filter-peptide-terms

Remove high-simplicity terms.

init-config-file

Initialize a configuration file.

install-demo-scripts

Copy demo scripts to the current directory.

intersect-peptide-terms

Find intersecting terms from multiple sets.

label-set

Define label associated with a set.

peptide-simplicity-mask

Lower-case high-simplicity regions in FASTA.

search-peptide-occurrances

Find signatures in peptide space.

set-simplicity-window

Define size of window used in simplicity calcs.

set-plot-type

Define label associated with a set.

set-simplicity-type

Select function used in simplicity calculation.

show-config

Print location and contents of config file.

show-context-object

Print the global context object.

test-logging

Logs at different severity levels.

Examples

Bash scripts that implement examples for calculating and using signature sets for Firmicutes and Streptococcus, complete with downloading data from GenBank, will be created in the (empty) current working directory when you issue the command:

aakbar install-demo-scripts

On linux and MacOS, follow the instructions to run the demos. On Windows, you will need bash installed for the scripts to work.

Tools

In addition to pyfastaq, two tools that you will probably find helpful in working with aakbar are alphabetsoup <https://github.com/ncgr/alphabetsoup> for sanitizing input FASTA files and tsv-tools <https://https://github.com/eBay/tsv-utils/> for filtering output TSV files.

Latest Release

Python package

Akbar the Great

GitHub

GitHub repository

License

License terms

Documentation

Documentation Server

Travis Build

Travis CI

Coverage

Codecov.io test coverage

Code Grade

Codacy.io grade

Dependencies

pyup.io dependencies

Issues

Issues reported

Project details


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