automlsa2
=========
.. image:: https://forthebadge.com/images/badges/built-with-science.svg
:alt: Made with science
:target: https://cgrb.oregonstate.edu
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:alt: Made with python
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:alt: GitHub commits since latest release (by date)
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:alt: Downloads per month
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:alt: Black format
:target: https://github.com/psf/black
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:alt: Checked with mypy
:target: http://mypy-lang.org/
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:target: https://github.com/davised/automlsa2/issues
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:alt: GitHub forks
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:alt: GitHub stars
:target: https://github.com/davised/automlsa2/stargazers
.. contents:: **Table of Contents**
:backlinks: none
Who might want this software?
-----------------------------
The intended audience is scientific researchers, computational biologists, and
bioinformaticians who are interested in exploring phylogenetic and phylogenomic
relationships between genes and organisms. The general idea is to allow the
input of sequence data along with marker genes and output a robust phylogenetic
tree. I've implemented commands to help with the installation of external
dependencies, and I hope the software is easy to use.
If you have feature requests or otherwise have ideas about how to make this
software better, please submit an issue with your ideas!
PhD/Masters students and undergraduates are especially encouraged to submit
issues if they are having trouble using this software.
Windows users, please install WSL to make use of this software. Using a Linux
distribution will make your life as a computational researcher significantly
easier.
Installation
------------
automlsa2 is distributed on `PyPI <https://pypi.org/project/automlsa2/>`_ as
a universal wheel and is available on Linux/macOS and Windows (untested) and
supports Python 3.7+ and PyPy.
.. code-block:: bash
$ python3 -m pip install -U automlsa2
While I will do my best to keep the git version usable, stick to a release
and/or pypi install for the most stable experience.
git version install:
.. code-block:: bash
$ git clone https://github.com/davised/automlsa2.git
$ cd automlsa2
$ python3 -m pip install -r requirements.txt
$ python3 -m pip install -U .
for developers, clone as above, then:
.. code-block:: bash
$ python3 -m pip install -e . --no-use-pep517
Dependencies
------------
Python modules:
1. pandas
2. numpy
3. biopython
4. rich
5. packaging
6. psutil
See ``requirements.txt`` for more info.
External programs:
1. `NCBI BLAST+ >= 2.10.0 <https://blast.ncbi.nlm.nih.gov>`_
2. `mafft >= 7.471 <https://mafft.cbrc.jp/alignment/software/>`_
3. `IQ-TREE COVID-19 release >= 2.1.1 <http://www.iqtree.org>`_
You can install external programs using the ``automlsa2 --install_deps``
command. These will be installed to ``${HOME}/.local/external`` unless
otherwise specified.
Just tell me how to run it
--------------------------
.. code-block:: bash
$ automlsa2 --files Genus_species_1.fna Genus_species_2.fna ... \
Genus_species_N.fna --query queries.fasta -t THREADS -- runID
Alternatively:
.. code-block:: bash
$ automlsa2 --dir path/to/genomes --query queries.fasta -t THREADS \
-- runID
Overview
--------
automlsa2 is a re-imagination of `autoMLSA.pl
<https://github.com/osuchanglab/autoMLSA>`_
The entire codebase has been re-written in python. While the general algorithm
produces similar output, and several steps are shared, there are many
updates and differences between the two programs, which will be covered later.
The general overview can be summarized here:
0. Input is a set of marker genes as queries, and a set of target genome FASTA
files.
1. BLAST databases are generated for each target genome, and each query gene
is extracted from the input query FASTA files.
2. BLAST searches are done with the extracted sequences and genomes.
3. Per genome hits are calculated pending the cut-offs, and genomes are
filtered from the analysis.
4. Sequences are extracted from the BLAST results as unaligned multi-FASTAs.
5. Unaligned sequences are aligned using mafft.
6. A nexus file is generated pointing to all aligned sequences.
7. A phylogenetic tree is generated using the nexus file as input.
BLAST searches are threaded, or, optionally, written to a file to be submitted
to a compute cluster. mafft alignment commands can also be written to a file
for submission to a compute cluster.
Input query files and genome directories are scanned for updates - if
sequences are added, removed, or changed, the analysis is re-done.
Multiple queries targeting the same gene sequence can be used to improve
coverage of disparate gene sequences, e.g. attempting to cover an entire
phylum with multiple reference genomes being used.
Usage
-----
.. code-block:: bash
$ automlsa2 -h
usage: automlsa2 [-h] [--query QUERY [QUERY ...]] [--files FILES [FILES ...]]
[--dir DIR [DIR ...]] [-e EVALUE] [-c COVERAGE] [-i IDENTITY]
[-p {blastn,tblastn}] [--config CONFIG] [--missing_check]
[-t THREADS] [--dups] [--allow_missing ALLOW_MISSING]
[--outgroup OUTGROUP] [--protect]
[--checkpoint {validate,preblast,filtering,prealign,postalign,nexus,none}]
[--install_deps [INSTALL_DEPS]] [--external EXTERNAL]
[--mafft MAFFT] [--iqtree IQTREE] [--debug] [--version]
[--quiet]
runid
This is a rewrite of autoMLSA.pl. Generates automated multi-locus sequence analyses.
positional arguments:
runid Name of the run directory.
optional arguments:
-h, --help show this help message and exit
--query <QUERY [QUERY ...]> Path to file with input seq(s).
--files <FILES [FILES ...]> Path to the target genome FASTA files.
--dir <DIR [DIR ...]> Path to the target genome directory with FASTA files.
-e EVALUE, --evalue EVALUE E-value cutoff for BLAST searches. [1e-5]
-c COVERAGE, --coverage COVERAGE Sets the coverage cut-off threshold. [50]
-i IDENTITY, --identity IDENTITY Sets the identity cut-off threshold. [30]
-p PROGRAM, --program PROGRAM Which BLAST program to run. [tblastn] {tblastn, blastn}
--config CONFIG Path to configuration json file to copy.
--missing_check Use this to confirm that settings have been
checked when genes are missing.
-t THREADS, --threads THREADS Number of threads to use. [1]
--dups Allow for duplicate query names for more sequence
coverage across disparate organisms.
--allow_missing ALLOW_MISSING Allow for N missing genes per genome. [0]
--outgroup OUTGROUP Name of outgroup file or strain to root on.
--protect Save files from getting overwritten. By default, as input
files update, older alignments and trees are deleted.
--checkpoint CHECKPOINT Name of stage to stop computing on. [none]
{validate,preblast,filtering,prealign,postalign,nexus,none}
--install_deps <[INSTALL_DEPS]> Install dependencies into given directory. [~/.local/external]
--external EXTERNAL Path to installed external programs. [~/.local/external]
--mafft MAFFT mafft settings [--localpair --maxiterate 1000 --reorder]
--iqtree IQTREE iqtree2 settings [-m MFP -B 1000 -alrt 1000 --msub
nuclear --merge rclusterf]
--debug Turn on debugging messages.
--version show program's version number and exit
--quiet Turn off progress messages.
One or more input target genome FASTA files is required, either using
``--files`` or ``--dir``. Additionally, one or more query FASTA files
containing one or more query gene sequences is necessary for analysis.
By default, protein queries are expected, and nucleotide FASTA sequence is
required for the target genomes. ``tblastn`` is used to target the genome
sequences using the amino acid queries. ``blastn`` is also available, targeting
the genome sequences using nucleotide queries.
Threads will speed things up significantly. BLAST searches are threaded in
python; submitting multiple threads to the blast executable often does not
result in much speed up, so each BLAST search is run with one CPU given.
Query marker genes often come from a well-studied representative of, at most,
the same genus. Intergenera phylogenies should have a representative sequence
from each genus. This can be accomplished by giving all examples of a
particular gene the same name in the reference FASTA file. e.g.
.. code-block:: bash
>Gene1 Refgenus1 refspecies ABC
<AA sequence>
>Gene1 Refgenus2 refspecies DEF
<AA sequence>
>Gene1 Refgenus3 refspecies GHI
<AA sequence>
This ^ FASTA ^ file would have three representatives of Gene1 in the analysis.
The resulting alignments would have one copy of the gene, with the best hits
from each target genome included.
Target genome files will be named based on the filename in the final output.
Generally, one will want to have Genus_species_strain.fasta or
G_species_strain.fasta as the filenames prior to analysis.
Genomes can be downloaded using my ``get_assemblies`` program, here:
https://pypi.org/project/get-assemblies/. Locally produced genomes can be
renamed as required.
Running Tests
-------------
The test data are included in a separate repository -
https://github.com/davised/automlsa2-examples
To download this test data, you can run ``git submodule update --init``.
Alternatively, you can run the ``run_tests.sh`` script and it will download
the git submodule for you and run the test command.
The tests should take about 2-3 minutes with 4 CPUs.
TODO
----
☐ Write detailed list of intermediate files.
☐ Compare functionality of this version to prior autoMLSA.pl version.
☑ Check for version numbers for external programs.
Contributing
------------
Bug reports are encouraged! Submit a github issue and I'll be happy to take
a look. Also, feel free to clone and submit merge requests.
Author Contact
--------------
`Ed Davis <mailto:ed@cgrb.oregonstate.edu>`_
Acknowledgments
----------------
Special thanks for helping me test the software and get the python code packaged:
* `Alex Weisberg <https://github.com/alexweisberg>`_
* `Shawn O'Neil <https://github.com/oneilsh>`_
Also, thanks to these groups for supporting me through my scientific career:
* `OSU Chang Lab <https://github.com/osuchanglab>`_
* `Center for Genome Research and Biocomputing @ OSU <https://cgrb.oregonstate.edu>`_
License
-------
automlsa2 is distributed under the terms listed in the ``LICENSE`` file. The
software is free for non-commercial use.
Copyrights
----------
Copyright (c) 2020 Oregon State University
All Rights Reserved.
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"description": "automlsa2\n=========\n\n.. image:: https://forthebadge.com/images/badges/built-with-science.svg\n :alt: Made with science\n :target: https://cgrb.oregonstate.edu\n.. image:: https://img.shields.io/github/v/release/davised/automlsa2\n :alt: GitHub version\n :target: https://github.com/davised/automlsa2/releases/latest\n.. image:: https://img.shields.io/pypi/v/automlsa2\n :alt: PyPI package version\n :target: https://pypi.org/project/automlsa2\n.. image:: https://img.shields.io/github/release-date/davised/automlsa2\n :alt: GitHub Release Date\n :target: https://github.com/davised/automlsa2/releases\n.. image:: https://img.shields.io/badge/Maintained%3F-yes-green.svg\n :alt: Maintained? Yes\n :target: https://github.com/davised/automlsa2/graphs/commit-activity\n.. image:: https://img.shields.io/badge/Made%20with-Python-1f425f.svg\n :alt: Made with python\n :target: https://python.org\n.. image:: https://img.shields.io/lgtm/grade/python/g/davised/automlsa2.svg?logo=lgtm&logoWidth=18\n :alt: Language grade: Python\n :target: https://lgtm.com/projects/g/davised/automlsa2/context:python\n.. image:: https://img.shields.io/github/last-commit/davised/automlsa2\n :alt: Latest commit\n :target: https://github.com/davised/automlsa2/commits\n.. image:: https://img.shields.io/github/commits-since/davised/automlsa2/latest\n :alt: GitHub commits since latest release (by date)\n :target: https://github.com/davised/automlsa2/commits/main\n.. image:: https://img.shields.io/pypi/dm/automlsa2\n :alt: Downloads per month\n :target: https://pypistats.org/packages/automlsa2\n.. image:: https://img.shields.io/tokei/lines/github/davised/automlsa2\n :alt: Lines of code\n :target: https://github.com/davised/automlsa2.git\n.. image:: https://img.shields.io/badge/code%20style-black-000000.svg\n :alt: Black format\n :target: https://github.com/psf/black\n.. image:: https://img.shields.io/badge/mypy-checked-blue\n :alt: Checked with mypy\n :target: http://mypy-lang.org/\n.. image:: https://img.shields.io/github/issues/davised/automlsa2\n :alt: GitHub issues\n :target: https://github.com/davised/automlsa2/issues\n.. image:: https://img.shields.io/github/forks/davised/automlsa2\n :alt: GitHub forks\n :target: https://github.com/davised/automlsa2/network\n.. image:: https://img.shields.io/github/stars/davised/automlsa2\n :alt: GitHub stars\n :target: https://github.com/davised/automlsa2/stargazers\n\n.. contents:: **Table of Contents**\n :backlinks: none\n\nWho might want this software?\n-----------------------------\n\nThe intended audience is scientific researchers, computational biologists, and\nbioinformaticians who are interested in exploring phylogenetic and phylogenomic\nrelationships between genes and organisms. The general idea is to allow the\ninput of sequence data along with marker genes and output a robust phylogenetic\ntree. I've implemented commands to help with the installation of external\ndependencies, and I hope the software is easy to use.\n\nIf you have feature requests or otherwise have ideas about how to make this\nsoftware better, please submit an issue with your ideas!\n\nPhD/Masters students and undergraduates are especially encouraged to submit\nissues if they are having trouble using this software.\n\nWindows users, please install WSL to make use of this software. Using a Linux\ndistribution will make your life as a computational researcher significantly\neasier.\n\nInstallation\n------------\n\nautomlsa2 is distributed on `PyPI <https://pypi.org/project/automlsa2/>`_ as\na universal wheel and is available on Linux/macOS and Windows (untested) and\nsupports Python 3.7+ and PyPy.\n\n.. code-block:: bash\n\n $ python3 -m pip install -U automlsa2\n\nWhile I will do my best to keep the git version usable, stick to a release\nand/or pypi install for the most stable experience.\n\ngit version install:\n\n.. code-block:: bash\n\n $ git clone https://github.com/davised/automlsa2.git\n $ cd automlsa2\n $ python3 -m pip install -r requirements.txt\n $ python3 -m pip install -U .\n\nfor developers, clone as above, then:\n\n.. code-block:: bash\n\n $ python3 -m pip install -e . --no-use-pep517\n\nDependencies\n------------\n\nPython modules:\n\n1. pandas\n2. numpy\n3. biopython\n4. rich\n5. packaging\n6. psutil\n\nSee ``requirements.txt`` for more info.\n\nExternal programs:\n\n1. `NCBI BLAST+ >= 2.10.0 <https://blast.ncbi.nlm.nih.gov>`_\n2. `mafft >= 7.471 <https://mafft.cbrc.jp/alignment/software/>`_\n3. `IQ-TREE COVID-19 release >= 2.1.1 <http://www.iqtree.org>`_\n\nYou can install external programs using the ``automlsa2 --install_deps``\ncommand. These will be installed to ``${HOME}/.local/external`` unless\notherwise specified.\n\nJust tell me how to run it\n--------------------------\n\n.. code-block:: bash\n\n $ automlsa2 --files Genus_species_1.fna Genus_species_2.fna ... \\\n Genus_species_N.fna --query queries.fasta -t THREADS -- runID\n\nAlternatively:\n\n.. code-block:: bash\n\n $ automlsa2 --dir path/to/genomes --query queries.fasta -t THREADS \\\n -- runID\n\n\nOverview\n--------\n\nautomlsa2 is a re-imagination of `autoMLSA.pl\n<https://github.com/osuchanglab/autoMLSA>`_\n\nThe entire codebase has been re-written in python. While the general algorithm\nproduces similar output, and several steps are shared, there are many\nupdates and differences between the two programs, which will be covered later.\n\nThe general overview can be summarized here:\n\n0. Input is a set of marker genes as queries, and a set of target genome FASTA\n files.\n1. BLAST databases are generated for each target genome, and each query gene\n is extracted from the input query FASTA files.\n2. BLAST searches are done with the extracted sequences and genomes.\n3. Per genome hits are calculated pending the cut-offs, and genomes are\n filtered from the analysis.\n4. Sequences are extracted from the BLAST results as unaligned multi-FASTAs.\n5. Unaligned sequences are aligned using mafft.\n6. A nexus file is generated pointing to all aligned sequences.\n7. A phylogenetic tree is generated using the nexus file as input.\n\nBLAST searches are threaded, or, optionally, written to a file to be submitted\nto a compute cluster. mafft alignment commands can also be written to a file\nfor submission to a compute cluster.\n\nInput query files and genome directories are scanned for updates - if\nsequences are added, removed, or changed, the analysis is re-done.\n\nMultiple queries targeting the same gene sequence can be used to improve\ncoverage of disparate gene sequences, e.g. attempting to cover an entire\nphylum with multiple reference genomes being used.\n\nUsage\n-----\n\n.. code-block:: bash\n\n $ automlsa2 -h\n usage: automlsa2 [-h] [--query QUERY [QUERY ...]] [--files FILES [FILES ...]]\n [--dir DIR [DIR ...]] [-e EVALUE] [-c COVERAGE] [-i IDENTITY]\n [-p {blastn,tblastn}] [--config CONFIG] [--missing_check]\n [-t THREADS] [--dups] [--allow_missing ALLOW_MISSING]\n [--outgroup OUTGROUP] [--protect]\n [--checkpoint {validate,preblast,filtering,prealign,postalign,nexus,none}]\n [--install_deps [INSTALL_DEPS]] [--external EXTERNAL]\n [--mafft MAFFT] [--iqtree IQTREE] [--debug] [--version]\n [--quiet]\n runid\n\n This is a rewrite of autoMLSA.pl. Generates automated multi-locus sequence analyses.\n\n positional arguments:\n runid Name of the run directory.\n\noptional arguments:\n\n-h, --help show this help message and exit\n--query <QUERY [QUERY ...]> Path to file with input seq(s).\n--files <FILES [FILES ...]> Path to the target genome FASTA files.\n--dir <DIR [DIR ...]> Path to the target genome directory with FASTA files.\n-e EVALUE, --evalue EVALUE E-value cutoff for BLAST searches. [1e-5]\n-c COVERAGE, --coverage COVERAGE Sets the coverage cut-off threshold. [50]\n-i IDENTITY, --identity IDENTITY Sets the identity cut-off threshold. [30]\n-p PROGRAM, --program PROGRAM Which BLAST program to run. [tblastn] {tblastn, blastn}\n--config CONFIG Path to configuration json file to copy.\n--missing_check Use this to confirm that settings have been\n checked when genes are missing.\n-t THREADS, --threads THREADS Number of threads to use. [1]\n--dups Allow for duplicate query names for more sequence\n coverage across disparate organisms.\n--allow_missing ALLOW_MISSING Allow for N missing genes per genome. [0]\n--outgroup OUTGROUP Name of outgroup file or strain to root on.\n--protect Save files from getting overwritten. By default, as input\n files update, older alignments and trees are deleted.\n--checkpoint CHECKPOINT Name of stage to stop computing on. [none]\n {validate,preblast,filtering,prealign,postalign,nexus,none}\n--install_deps <[INSTALL_DEPS]> Install dependencies into given directory. [~/.local/external]\n--external EXTERNAL Path to installed external programs. [~/.local/external]\n--mafft MAFFT mafft settings [--localpair --maxiterate 1000 --reorder]\n--iqtree IQTREE iqtree2 settings [-m MFP -B 1000 -alrt 1000 --msub\n nuclear --merge rclusterf]\n--debug Turn on debugging messages.\n--version show program's version number and exit\n--quiet Turn off progress messages.\n\nOne or more input target genome FASTA files is required, either using\n``--files`` or ``--dir``. Additionally, one or more query FASTA files\ncontaining one or more query gene sequences is necessary for analysis.\n\nBy default, protein queries are expected, and nucleotide FASTA sequence is\nrequired for the target genomes. ``tblastn`` is used to target the genome\nsequences using the amino acid queries. ``blastn`` is also available, targeting\nthe genome sequences using nucleotide queries.\n\nThreads will speed things up significantly. BLAST searches are threaded in\npython; submitting multiple threads to the blast executable often does not\nresult in much speed up, so each BLAST search is run with one CPU given.\n\nQuery marker genes often come from a well-studied representative of, at most,\nthe same genus. Intergenera phylogenies should have a representative sequence\nfrom each genus. This can be accomplished by giving all examples of a\nparticular gene the same name in the reference FASTA file. e.g.\n\n.. code-block:: bash\n\n >Gene1 Refgenus1 refspecies ABC\n <AA sequence>\n >Gene1 Refgenus2 refspecies DEF\n <AA sequence>\n >Gene1 Refgenus3 refspecies GHI\n <AA sequence>\n\nThis ^ FASTA ^ file would have three representatives of Gene1 in the analysis.\nThe resulting alignments would have one copy of the gene, with the best hits\nfrom each target genome included.\n\nTarget genome files will be named based on the filename in the final output.\nGenerally, one will want to have Genus_species_strain.fasta or\nG_species_strain.fasta as the filenames prior to analysis.\n\nGenomes can be downloaded using my ``get_assemblies`` program, here:\nhttps://pypi.org/project/get-assemblies/. Locally produced genomes can be\nrenamed as required.\n\nRunning Tests\n-------------\n\nThe test data are included in a separate repository -\nhttps://github.com/davised/automlsa2-examples\n\nTo download this test data, you can run ``git submodule update --init``.\n\nAlternatively, you can run the ``run_tests.sh`` script and it will download\nthe git submodule for you and run the test command.\n\nThe tests should take about 2-3 minutes with 4 CPUs.\n\nTODO\n----\n\n\u2610 Write detailed list of intermediate files.\n\n\u2610 Compare functionality of this version to prior autoMLSA.pl version.\n\n\u2611 Check for version numbers for external programs.\n\nContributing\n------------\n\nBug reports are encouraged! Submit a github issue and I'll be happy to take\na look. Also, feel free to clone and submit merge requests.\n\nAuthor Contact\n--------------\n\n`Ed Davis <mailto:ed@cgrb.oregonstate.edu>`_\n\nAcknowledgments\n----------------\n\nSpecial thanks for helping me test the software and get the python code packaged:\n\n* `Alex Weisberg <https://github.com/alexweisberg>`_\n* `Shawn O'Neil <https://github.com/oneilsh>`_\n\nAlso, thanks to these groups for supporting me through my scientific career:\n\n* `OSU Chang Lab <https://github.com/osuchanglab>`_\n* `Center for Genome Research and Biocomputing @ OSU <https://cgrb.oregonstate.edu>`_\n\nLicense\n-------\n\nautomlsa2 is distributed under the terms listed in the ``LICENSE`` file. The\nsoftware is free for non-commercial use.\n\nCopyrights\n----------\n\nCopyright (c) 2020 Oregon State University\n\nAll Rights Reserved.\n\n\n",
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