Pasta
PASTA (Practical Alignment using SATe and Transitivity)
Install / Use
/learn @smirarab/PastaREADME
This is an implementation of the PASTA (Practical Alignment using Saté and TrAnsitivity) algorithm published in RECOMB-2014 and JCB:
- Mirarab S, Nguyen N, Warnow T. PASTA: ultra-large multiple sequence alignment. Sharan R, ed. Res Comput Mol Biol. 2014:177-191.
- Mirarab S, Nguyen N, Guo S, Wang L-S, Kim J, Warnow T. PASTA: Ultra-Large Multiple Sequence Alignment for Nucleotide and Amino-Acid Sequences. J Comput Biol. 2015;22(5):377-386. doi:10.1089/cmb.2014.0156.
The latest version includes a new decomposition technique described here:
- Balaban, Metin, Niema Moshiri, Uyen Mai, and Siavash Mirarab. “TreeCluster : Clustering Biological Sequences Using Phylogenetic Trees.” BioRxiv, 2019, 591388. doi:10.1101/591388.
Contact:
All questions and inquires should be addressed to our user email group: pasta-users@googlegroups.com. Please check our Tutorial and previous posts before sending new requests.
Developers
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The code and the algorithm are developed by Siavash Mirarab and Tandy Warnow, with help from Nam Nguyen. The latest version of the code includes a new code decomposition designed and implemented by Uyen Mai.
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The current PASTA code is heavily based on the SATé code developed by Mark Holder's group at KU. Refer to sate-doc directory for documentation of the SATé code, including the list of authors, license, etc.
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Niema Moshiri has contributed to the import to dendropy 4 and python 3 and to the Docker image.
Documentation
In addition to this README file, you can consult this Tutorial.
INSTALLATION
You have three options
1. From Source Code
- The current version of PASTA has been developed and tested entirely on Linux and MAC.
- Windows won't work currently (future versions may or may not support Windows).
You need to have:
- Python (version 2.7 or later, including python 3)
- Dendropy (but the setup script should automatically install dendropy for you if you don't have it)
- Java (only required for using OPAL)
- wxPython - only required if you want to use the GUI. The setup script does not automatically install this.
Installation steps:
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Open a terminal and create a directory where you want to keep PASTA and go to this directory. For example:
mkdir ~/pasta-code cd ~/pasta-code` -
Clone the PASTA code repository from our github repository. For example you can use:
git clone https://github.com/smirarab/pasta.gitIf you don't have git, you can directly download a zip file from the repository and decompress it into your desired directory.
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A. Clone the relevant "tools" directory (these are also forked from the SATé project). There are different repositories for linux and MAC. You can use
git clone https://github.com/smirarab/sate-tools-linux.git #for Linuxor
git clone https://github.com/smirarab/sate-tools-mac.git. #for MACOr you can directly download these as zip files for Linux or MAC and decompress them in your target directory (e.g.
pasta-code).- Note that the tools directory and the PASTA code directory should be under the same parent directory.
- When you use the zip files instead of using
git, after decompressing the zip file you may get a directory calledsate-tools-mac-masterorsate-tools-linux-masterinstead ofsate-tools-macorsate-tools-linux. You need to rename these directories and remove the-masterpart. - Those with 32-bit Linux machines need to be aware that the master branch has 64-bit binaries. 32-bit binaries are provided in the
32bitbranch ofsate-tools-linuxgit project (so download this zip file instead).
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B. (Optional) Only if you want to use MAFFT-Homologs within PASTA:
cd sate-tools-linuxorcd sate-tools-macUsegit clone https://github.com/koditaraszka/pasta-databasesor download directly athttps://github.com/koditaraszka/pasta-databases.git- Be sure to leave this directory
cd ..before starting the next step
- Be sure to leave this directory
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cd pasta(orcd pasta-masterif you used the zip file instead of clonning the git repository) -
Then run:
sudo python setup.py developIf you don't have root access, use:
python setup.py develop --userCommon Problems:
Could not find SATé tools bundle directory: this means you don't have the right tools directory at the right location. Maybe you downloaded MAC instead of Linux? Or, maybe you didn't put the directory in the parent directory of where pasta code is? Most likely, you used the zip files and forgot to remove teh-masterfrom the directory name. Runmv sate-tools-mac-master sate-tools-macon MAC ormv sate-tools-linux-master sate-tools-linuxto fix this issue.- The
setup.pyscript is supposed to install setuptools for you if you don't have it. This sometimes works and sometimes doesn't. If you get an error with a message likeinvalid command 'develop', it means that setuptools is not installed. To solve this issue, you can manually install setup tools. For example, on Linux, you can runcurl https://bootstrap.pypa.io/ez_setup.py -o - | sudo python(but note there are other ways of installing setuptools as well).
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Pasta now includes additional aligners for Linux and MAC users: mafft-ginsi, mafft-homologs, contralign (version 1), and probcons. In order to use mafft-homologs and contralign, the user must set the environment variable
CONTRALIGN_DIR=/dir/to/sate-tools-linux. You can useexport CONTRALIGN_DIR=/dir/to/sate-tools-linuxor just edit~/.bashrcto haveCONTRALIGN_DIR=dir/to/sate-tools-linux.- To use these aligners, add the following to your pasta execution
--aligner=NAME_OF_ALIGNER, whereNAME_OF_ALIGNERnow includes (ginsi,homologs,contralign, andprobcons)
- To use these aligners, add the following to your pasta execution
2. From Docker
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Make sure you have Docker installed
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Run
docker pull smirarab/pasta
You are done. You can test using
docker run smirarab/pasta run_pasta.py -h
3. Conda:
Please see https://anaconda.org/bioconda/pasta
You should be good with:
conda install bioconda::pasta
Email pasta-users@googlegroups.com for installation issues.
EXECUTION
To run PASTA using the command-line:
python run_pasta.py -i input_fasta [-t starting_tree]
PASTA by default picks the appropriate configurations automatically for you. The starting tree is optional. If not provided, PASTA estimates a starting tree.
Run
python run_pasta.py --help
to see PASTA's various options and descriptions of how they work.
To run the GUI version,
- if you have installed from the source code, cd into your installation directory and run
python run_pasta_gui.py
on some machines you may instead need to use
pythonw run_pasta_gui.py
To run PASTA using Docker, run
docker run -v [path to the directory with your input files]:/data smirarab/pasta run_pasta.py -i input_fasta [-t starting_tree]
On Windows, you may have to enable drive sharing; see Shared Drives on this page.
Options
PASTA estimates alignments and maximum likelihood (ML) trees from unaligned sequences using an iterative approach. In each iteration, it first estimates a multiple sequence alignment and then a ML tree is estimated on (a masked version of) the alignment. By default PASTA performs 3 iterations, but a host of options enable changing that behavior. In each iteration, a divide-and-conquer strategy is used for estimating the alignment. The set of sequences is divided into smaller subsets, each of which is aligned using an external alignment tool (the default is MAFFT-L-ins-i). These subset alignments are then pairwise merged (by default using Opal) and finally the pairwise merged alignments are merged into a final alignment using transitivity merge. The division of the dataset into smaller subsets and selecting which alignments should be pairwise merged is guided by the tree from the previous iteration. The first step therefore needs an initial tree.
When GUI is used, a limited set of important options can be adjusted. The command line also allows you to alter the behavior of the algorithm, and provides a larger sets of options that can be adjusted.
Options can also be passed in as configuration files with the format:
[commandline]
option-name = value
[sate]
option-name = value
With every run, PASTA saves the configuration file for that run as a temporary
file called [jobname]_temp_pasta_config.txt in your output directory.
Multiple configuration files can be provided. Configuration files are read in the order they occur as arguments (with values in later files replacing previously read values). Options specified in the command line are read last. Thus, these values "overwrite" any settings from the configuration files.
Note: the use of --auto option can overwrite some of the other options provided by comman
