aakbar -- amino-acid k-mer signature tools


Keywords
science
License
BSD-1-Clause
Install
pip install aakbar==0.15

Documentation

aakbar

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
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