Python module for average nucleotide identity analyses
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README.md

README.md (pyani)

pyani PyPi version pyani licence pyani TravisCI build status pyani codecov.io coverage

Overview

pyani is a Python3 module that provides support for calculating average nucleotide identity (ANI) and related measures for whole genome comparisons, and rendering relevant graphical summary output. Where available, it takes advantage of multicore systems, and can integrate with SGE/OGE-type job schedulers for the sequence comparisons.

pyani installs the following scripts into the $PATH:

  • average_nucleotide_identity.py that enables command-line ANI analysis.
  • genbank_get_genomes_by_taxon.py that downloads publicly-available genomes from NCBI.
  • delta_filter_wrapper.py is a helper script required to run delta-filter on SGE/OGE systems.

Installation

The easiest way to install pyani is to use pip3:

pip3 install pyani

From version 0.1.3.2 onwards, this should also install all the required Python package dependencies. Prior to this version (i.e. 0.1.3.1 and earlier), you can acquire these dependencies with pip -r, and pointing at requirements.txt from this repository:

pip3 install -r requirements.txt

Docker images

pyani's scripts are also provided as Docker images, that can be run locally as containers. To use these images, first install Docker, then to run the corresponding scripts issue either:

docker run -v ${PWD}:/host_dir leightonpritchard/average_nucleotide_identity

or

docker run -v ${PWD}:/host_dir leightonpritchard/genbank_get_genomes_by_taxon

The -v ${PWD}:/host_dir argument enables the Docker container to see the current directory. Without this argument, the container will not be able to see your input files, or write output data.

Testing pyani

pyani includes tests that can be run with nosetest (including coverage measurement using coverage.py) with the following command, executed from the repository root directory:

nosetests --cover-erase --cover-package=pyani --cover-html --with-coverage

Coverage output will be placed (by default) in the cover subdirectory, and can be loaded into the web browser.

Running pyani

Script: average_nucleotide_identity.py

The average_nucleotide_identity.py script - installed as part of this package - enables straightforward ANI analysis at the command-line, and uses the pyani module behind the scenes.

You can get a summary of available command-line options with average_nucleotide_identity.py -h

$ average_nucleotide_identity.py -h
usage: average_nucleotide_identity.py [-h] [-o OUTDIRNAME] [-i INDIRNAME] [-v]
                                      [-f] [-s FRAGSIZE] [-l LOGFILE]
                                      [--skip_nucmer] [--skip_blastn]
                                      [--noclobber] [--nocompress] [-g]
                                      [--gformat GFORMAT] [--gmethod GMETHOD]
                                      [--labels LABELS] [--classes CLASSES]
                                      [-m METHOD] [--scheduler SCHEDULER]
                                      [--workers WORKERS]
                                      [--SGEgroupsize SGEGROUPSIZE]
                                      [--maxmatch] [--nucmer_exe NUCMER_EXE]
                                      [--blastn_exe BLASTN_EXE]
                                      [--makeblastdb_exe MAKEBLASTDB_EXE]
                                      [--blastall_exe BLASTALL_EXE]
                                      [--formatdb_exe FORMATDB_EXE]
                                      [--write_excel] [--subsample SUBSAMPLE]
                                      [--seed SEED] [--jobprefix JOBPREFIX]


[…]

Example data and output can be found in the directory test_ani_data. The data are chromosomes of four isolates of Caulobacter. Basic analyses can be performed with the command lines:

$ average_nucleotide_identity.py -i tests/test_ani_data/ -o tests/test_ANIm_output -m ANIm -g
$ average_nucleotide_identity.py -i tests/test_ani_data/ -o tests/test_ANIb_output -m ANIb -g
$ average_nucleotide_identity.py -i tests/test_ani_data/ -o tests/test_ANIblastall_output -m ANIblastall -g
$ average_nucleotide_identity.py -i tests/test_ani_data/ -o tests/test_TETRA_output -m TETRA -g

The graphical output below, supporting assignment of NC_002696 and NC_011916 to the same species (C.crescentus), and the other two isolates to distinct species (NC_014100:C.segnis; NC_010338:C. sp K31), was generated with the command-line:

average_nucleotide_identity.py -v -i tests/test_ani_data/ \
    -o tests/test_ANIm_output/ -g --gformat png,pdf,eps \
    --classes tests/test_ani_data/classes.tab \
    --labels tests/test_ani_data/labels.tab

ANIm percentage identity for Caulobacter test data ANIm alignment coverage for Caulobacter test data ANIm alignment length for Caulobacter test data ANIm alignment similarity errors for Caulobacter test data

Script: genbank_get_genomes_by_taxon.py

The script genbank_get_genomes_by_taxon.py, installed by this package, enables download of genomes from NCBI, specified by taxon ID. The script will download all available assemblies for taxa at or below the specified node in the NCBI taxonomy tree.

Command-line options can be viewed using:

$ genbank_get_genomes_by_taxon.py -h
usage: genbacnk_get_genomes_by_taxon.py [-h] [-o OUTDIRNAME] [-t TAXON] [-v]
                                        [-f] [--noclobber] [-l LOGFILE]
                                        [--format FORMAT] [--email EMAIL]
                                        [--retries RETRIES]
                                        [--batchsize BATCHSIZE]
[…]

For example, the NCBI taxonomy ID for Caulobacter is 75, so all publicly-available Caulobacter sequences can be obtained using the command-line:

$ genbank_get_genomes_by_taxon.py -o Caulobacter_downloads -v -t 75 -l Caulobacter_downloads.log --email me@my.email.domain
INFO: genbank_get_genomes_by_taxon.py: Mon Apr 18 17:22:54 2016
INFO: command-line: /Users/lpritc/Virtualenvs/pyani3/bin/genbank_get_genomes_by_taxon.py -o Caulobacter_downloads -v -t 75 -l Caulobacter_downloads.log --email me@my.email.domain
INFO: Namespace(batchsize=10000, email='me@my.email.domain', force=False, format='gbk,fasta', logfile='Caulobacter_downloads.log', noclobber=False, outdirname='Caulobacter_downloads', retries=20, taxon='75', verbose=True)
INFO: Set NCBI contact email to me@my.email.domain
INFO: Creating directory Caulobacter_downloads
INFO: Output directory: Caulobacter_downloads
INFO: Passed taxon IDs: 75
INFO: Entrez ESearch with query: txid75[Organism:exp]
INFO: Entrez ESearch returns 29 assembly IDs
INFO: Identified 29 unique assemblies
INFO: Taxon 75: 29 assemblies
[…]
INFO: Assembly 639581: 271 contigs
INFO: Assembly 233261: 17 contigs
INFO: Assembly 575291: 48 contigs
INFO: Mon Apr 18 17:25:46 2016
INFO: Done.

NOTE: You must provide a valid email to identify yourself to NCBI for troubleshooting.

The number of attempted retries for each download, and the size of a batch download can be modified. By default, the script will attempt 20 download retries, and obtain sequences in batches of 10000.

DEPENDENCIES

Note that Python package dependencies should automatically be installed if you are using version 0.1.3.2 or greater, and installing with pip install pyani.

For earlier versions, you can satisfy dependencies by using pip install -r requirements.txt (using the requirements.txt file in this repository).

For ANI analysis

Alignment tools

  • BLAST+ executable in the $PATH, or available on the command line (required for ANIb analysis) ftp://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/
  • legacy BLAST executable in the $PATH or available on the command line (required for ANIblastall analysis) ftp://ftp.ncbi.nlm.nih.gov/blast/executables/release/LATEST/
  • MUMmer executables in the $PATH, or available on the command line (required for ANIm analysis) http://mummer.sourceforge.net/

For graphical output

Method and Output Description

Average Nucleotide Identity (ANI)

This module calculates Average Nucleotide Identity (ANI) according to one of a number of alternative methods described in, e.g.

  • Richter M, Rossello-Mora R (2009) Shifting the genomic gold standard for the prokaryotic species definition. Proc Natl Acad Sci USA 106: 19126-19131. doi:10.1073/pnas.0906412106. (ANI1020, ANIm, ANIb)
  • Goris J, Konstantinidis KT, Klappenbach JA, Coenye T, Vandamme P, et al. (2007) DNA-DNA hybridization values and their relationship to whole-genome sequence similarities. Int J Syst Evol Micr 57: 81-91. doi:10.1099/ijs.0.64483-0.

ANI is proposed to be the appropriate in silico substitute for DNA-DNA hybridisation (DDH), and so useful for delineating species boundaries. A typical percentage threshold for species boundary in the literature is 95% ANI (e.g. Richter et al. 2009).

All ANI methods follow the basic algorithm:

  • Align the genome of organism 1 against that of organism 2, and identify the matching regions
  • Calculate the percentage nucleotide identity of the matching regions, as an average for all matching regions

Methods differ on: (1) what alignment algorithm is used, and the choice of parameters (this affects the aligned region boundaries); (2) what the input is for alignment (typically either fragments of fixed size, or the most complete assembly available).

  • ANIm: uses MUMmer (NUCmer) to align the input sequences.
  • ANIb: uses BLASTN+ to align 1020nt fragments of the input sequences
  • ANIblastall: uses legacy BLASTN to align 1020nt fragments of the input sequences
  • TETRA: calculates tetranucleotide frequencies of each input sequence

The algorithms takes as input correctly-formatted FASTA multiple sequence files. All sequences for a single organism should be contained in only one sequence file. Although it is possible to provide new labels for each input genome, for rendering graphical output, the names of these files are used for identification so it is best to name them sensibly.

Output is written to a named directory. The output files differ depending on the chosen ANI method.

  • ANIm: MUMmer/NUCmer .delta files, describing each pairwise sequence alignment. Output as tab-separated plain text format tables describing: alignment coverage; total alignment lengths; similarity errors; and percentage identity (ANIm).
  • ANIb and ANIblastall: FASTA sequences describing 1020nt fragments of each input sequence; BLAST nucleotide databases - one for each set of fragments; and BLASTN output files (tab-separated tabular format plain text) - one for each pairwise comparison of input sequences. Output as tab-separated plain text tables describing: alignment coverage; total alignment lengths; similarity errors; and percentage identity (ANIb or ANIblastall).
  • TETRA: Tab-separated plain text files describing the Pearson correlations between Z-score distributions for each tetranucleotide in each input sequence (TETRA).

If graphical output is chosen, the output directory will also contain PDF, PNG and EPS files representing the various output measures as a heatmap with row and column dendrograms. Other output formats (e.g. SVG) can be specified with the --gformat argument.

Developer notes

The pyani package is presented at GitHub under two main branches:

  • master is the source code underpinning the most recent/current release of pyani. It will (almost) always be in sync with the latest release found at https://github.com/widdowquinn/pyani/releases. The only time this code should not be in sync with the release is when there are modifications to documentation, or immediately preceding a release.
  • development is the current bleeding-edge version of pyani. It should (almost) always be in a working and usable condition, but may not be complete and/or some features may be missing or still under development.

### Code Style and Pre-Commit Hooks

The source code for pyani is expected to conform to flake8 linting, and black code styling. These are enforced as pre-commit hooks using the pre-commit package (included in requirements.txt).

The black and flake8 hooks are defined in .pre-commit-config.yaml. Custom settings for flake8 are held in .flake8.

To enable pre-commit checks in the codebase on your local machine, execute the following command in the root directory of this repository:

pre-commit install

Licensing

Unless otherwise indicated, all code is subject to the following agreement:

(c) The James Hutton Institute 2014-2018
Author: Leighton Pritchard

Contact: leighton.pritchard@hutton.ac.uk

Address: 
Leighton Pritchard,
Information and Computational Sciences,
James Hutton Institute,
Errol Road,
Invergowrie,
Dundee,
DD6 9LH,
Scotland,
UK

The MIT License

Copyright (c) 2014-2018 The James Hutton Institute

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.