README.md
In DomBennett/om..pasta: Outsider module for running pasta
Run pasta with outsider in R
pasta (Practical Alignment using SATe and Transitivity): Multiple
sequence alignment of biological sequences.
Install and look up help
library(outsider)
#> ----------------
#> outsider v 0.1.0
#> ----------------
#> - Security notice: be sure of which modules you install
module_install(repo = "dombennett/om..pasta")
#> -----------------------------------------------------
#> Warning: You are about to install an outsider module!
#> -----------------------------------------------------
#> Outsider modules install and run external programs
#> via Docker <https://www.docker.com>. These external
#> programs may communicate with the internet and could
#> potentially be malicious.
#>
#> Be sure to know the module you are about to install:
#> Is it from a trusted developer? Are colleagues using
#> it? Is it supposed to download lots of data? Is it
#> well used (e.g. check number of stars on GitHub)?
#> -----------------------------------------------------
#> Module information
#> -----------------------------------------------------
#> program: pasta
#> details: PASTA (Practical Alignment using Sate and TrAnsitivity) algorithm.
#> docker: dombennett
#> github: dombennett
#> url: https://github.com/dombennett/om..pasta
#> image: dombennett/om_pasta
#> container: om_pasta
#> package: om..pasta
#> Travis CI: Passing
#> -----------------------------------------------------
#> Enter any key to continue or press Esc to quit
#module_help(repo = "dombennett/om..pasta")
Aligning a small set of DNA sequences
The below example is adapted from the PASTA
tutorial.
library(outsider)
# import
pasta <- module_import('pasta', repo = 'dombennett/om..pasta')
# get help
pasta('-h')
#> Usage: run_pasta.py [options] <settings_file1> <settings_file2> ...
#>
#>
#> PASTA performs iterative realignment and tree inference, similar to SATe, but
#> uses a very different merge algorithm which improves running time, memory
#> usage, and accuracy. The current code is heavily based on SATe, with lots of
#> modifications, many related to algorithmic differences between PASTA and SATe,
#> but also many scalability improvements (parallelization, tree parsing,
#> defaults, etc.)
#>
#> Minimally you must provide a sequence file (with the '--input' option); a
#> starting tree is optional. By default, important algorithmic parameters are
#> set based on automatic rules.
#>
#> The command line allows you to alter the behavior of the algorithm
#> (termination criteria, when the algorithm switches to "Blind" acceptance of
#> new alignments, how the tree is decomposed to find subproblems to be used, and
#> the external tools to use).
#>
#> 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.
#>
#> 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 that the use of --auto option can overwrite some
#> of the other options provided by commandline or through configuration files.
#>
#>
#> Options:
#> --version show program's version number and exit
#> -h, --help show this help message and exit
#>
#> commandline options:
#> -a, --aligned If used, then the input file be will treated as
#> aligned for the purposes of the first round of tree
#> inference (the algorithm will start with tree
#> searching on the input before re-aligning). This
#> option only applies if a starting tree is NOT given.
#> --alignment-suffix=ALIGNMENT-SUFFIX
#> suffix for alignment name (default: .marker001.[input
#> name].aln)
#> --auto This option is mostly for backward compatibility. If
#> used, then automatically identified default values for
#> the max_subproblem_size, number of cpus, tools,
#> breaking strategy, masking criteria, and stopping
#> criteria will be used. This is just like using the
#> default options. However, [WARNING] when auto option
#> is used PASTA overrides the value of these options
#> even if you have supplied them; we recommend that you
#> run this option with --exportconfig to see the exact
#> set of options that will be used in your analysis.
#> -d DATATYPE, --datatype=DATATYPE
#> Specify DNA, RNA, or Protein to indicate what type of
#> data is specified. Note that this option is NOT
#> automatically determined [default: dna]
#> --exportconfig=EXPORTCONFIG
#> Export the configuration to the specified file and
#> exit. This is useful if you want to combine several
#> configurations and command line settings into a single
#> configuration file to be used in other analyses.
#> -i INPUT, --input=INPUT
#> input sequence file
#> -j JOB, --job=JOB job name [pastajob]
#> --keepalignmenttemps
#> Keep even the realignment temporary running files
#> (this only has an effect if keeptemp is also
#> selected).
#> -k, --keeptemp Keep temporary running files? [default: disabled]
#> --missing=MISSING How to deal with missing data symbols. Specify either
#> "Ambiguous" or "Absent" if the input data contains
#> ?-symbols
#> -m, --multilocus Analyze multi-locus data? NOT SUPPORTED IN CURRENT
#> PASTA version.
#> --raxml-search-after
#> If used, the completion of the PASTA algorithm will be
#> followed by a tree search using RAxML on the masked
#> alignment. This can be useful if a very fast and
#> approximate tree estimator is used during the PASTA
#> algorithm. [default: disabled]
#> --temporaries=TEMPORARIES
#> directory that will be the parent for this job's
#> temporary file [default in PASTA home]
#> --timesfile=TIMESFILE
#> optional file that will store the times of events
#> during the PASTA run. If the file exists, new lines
#> will be
#> -t TREEFILE, --treefile=TREEFILE
#> starting tree file
#> --two-phase If used, then the program will not perform the PASTA
#> algorithm. Instead it will simply call the sequence
#> aligner to align the entire dataset then will call the
#> tree estimator to obtain the tree.
#> --untrusted If used, then the data in the input file will be
#> parsed using a more careful procedure. This will
#> generate more helpful error messages, but will use
#> more memory and be much slower for large inputs. If
#> this option is omitted, the error messages resulting
#> from invalid input data will be more cryptic.
#>
#> SATe acceptance options:
#> --blind-after-iter-without-imp=#
#> Maximum number of iterations without an improvement in
#> likelihood score that PASTA will run before switching
#> to blind mode. [default: disabled]
#> --blind-after-time-without-imp=#.#
#> Maximum time (in seconds) that PASTA will run without
#> an improvement in likelihood score before switching to
#> blind mode. [default: disabled]
#> --blind-after-total-iter=#
#> Maximum number of iterations that PASTA will run
#> before switching to blind mode. [default: 0]
#> --blind-after-total-time=#.#
#> Maximum time (in seconds) that PASTA will run before
#> switching to blind mode. [default: disabled]
#> --no-blind-mode-is-final
#> When the blind mode is final, then PASTA will never
#> leave blind mode once it is has entered blind mode.
#> --move-to-blind-on-worse-score
#> If True then PASTA will move to the blind mode as soon
#> it encounters a tree/alignment pair with a worse
#> score. This is essentially the same as running in
#> blind mode from the beginning, but it does allow one
#> to terminate a run at an interval from the first time
#> the algorithm fails to improve the score.
#>
#> SATe decomposition options:
#> --break-strategy=BREAK_STRATEGY
#> The method for choosing an edge when bisecting the
#> tree during decomposition [default: mincluster]
#> --max-subproblem-frac=#.#
#> The maximum size (number of leaves) of subproblems
#> specified in terms as a proportion of the total number
#> of leaves. When a subproblem contains this number of
#> leaves (or fewer), then it will not be decomposed
#> further. [default: automatically picked based on
#> alignment size]
#> --max-subproblem-size=#
#> The maximum size (number of leaves) of subproblems.
#> When a subproblem contains this number of leaves (or
#> fewer), then it will not be decomposed further.
#> [default: automatically picked based on alignment
#> size]
#> --max-subtree-diameter=#.#
#> The maximum diameter of each subtree. [default: 2.5]
#> --min-subproblem-size=#
#> The minimum size (number of leaves) of subproblems.
#> [default: 0]
#>
#> SATe filtering options:
#> --treeshrink-filter
#> If used, then the inferred FastTree will be filtered
#> by TreeShrink for long branch outliers.
#>
#> SATe output options:
#> -o OUTPUT_DIRECTORY, --output-directory=OUTPUT_DIRECTORY
#> directory for output files (defaults to input file
#> directory)
#> --no-return-final-tree-and-alignment
#> Return the best likelihood tree and alignment pair
#> instead of those from the last iteration; this is
#> discouraged with masking option enabled.
#>
#> SATe platform options:
#> --max-mem-mb=# The maximum memory available to OPAL (for the Java
#> heap size when running Java tools).
#> --num-cpus=# The number of processing cores that you would like to
#> assign to PASTA. This number should not exceed the
#> number of cores on your machine. [default: number of
#> cores available on the machine]
#>
#> SATe searching options:
#> --mask-gappy-sites=#
#> The minimum number of non-gap characters required in
#> each column passed to the tree estimation step.
#> Columns with fewer non-gap characters than the given
#> threshold will be masked out before passing the
#> alignment into the tree estimation module. These
#> columns will be present in the final alignment.
#> [default: 0.1% of alignment size]
#> --start-tree-search-from-current
#> If selected that the tree from the previous iteration
#> will be given to the tree searching tool as a starting
#> tree.
#>
#> SATe spaning-tree options:
#> --build-MST Construct the spanning tree using minimum spanning
#> tree algorithm [default: False]
#>
#> SATe termination options:
#> --after-blind-iter-term-limit=#
#> The maximum number of iteration that the PASTA
#> algorithm will run after PASTA has entered blind mode.
#> If the number is less than 1, then no iteration limit
#> will be used. [default: disabled]
#> --after-blind-iter-without-imp-limit=#
#> The maximum number of iterations without an
#> improvement in score that the PASTA algorithm will run
#> after entering BLIND mode. If the number is less than
#> 1, then no iteration limit will be used. [default:
#> disabled]
#> --after-blind-time-term-limit=#.#
#> Maximum time (in seconds) that PASTA will continue
#> starting new iterations of realigning and tree
#> searching after PASTA has entered blind mode. If the
#> number is less than 0, then no time limit will be
#> used. [default: disabled]
#> --after-blind-time-without-imp-limit=#.#
#> Maximum time (in seconds) since the last improvement
#> in score that PASTA will continue starting new
#> iterations of realigning and tree searching after
#> entering BLIND mode. If the number is less than 0,
#> then no time limit will be used. [default: disabled]
#> --iter-limit=# The maximum number of iteration that the PASTA
#> algorithm will run. If the number is less than 1,
#> then no iteration limit will be used. [default: 3]
#> --iter-without-imp-limit=#
#> The maximum number of iterations without an
#> improvement in score that the PASTA algorithm will
#> run. If the number is less than 1, then no iteration
#> limit will be used. [default: disabled]
#> --time-limit=#.# Maximum time (in seconds) that PASTA will continue
#> starting new iterations of realigning and tree
#> searching. If the number is less than 0, then no time
#> limit will be used. [default: disabled]
#> --time-without-imp-limit=#.#
#> Maximum time (in seconds) since the last improvement
#> in score that PASTA will continue starting new
#> iterations of realigning and tree searching. If the
#> number is less than 0, then no time limit will be
#> used. [default: disabled]
#>
#> SATe tools options:
#> --aligner=ALIGNER The name of the alignment program to use for
#> subproblems. [default: mafft]
#> --merger=MERGER The name of the alignment program to use to merge
#> subproblems. [default: OPAL]
#> --tree-estimator=TREE_ESTIMATOR
#> The name of the tree inference program to use to find
#> trees on fixed alignments. [default: fasttree]
# download
wd <- file.path(tempdir(), 'example_job')
if (!dir.exists(wd)) {
dir.create(wd)
}
# example DNA, based on MAFFT example
seq_file <- file.path(wd, 'example_seq.fasta')
url <- 'https://raw.githubusercontent.com/DomBennett/om..pasta/master/example_seq.fasta'
download.file(url = url, destfile = seq_file)
# run DNA alignment
pasta(arglist = c('-i', seq_file, '-d', 'dna',
'--alignment-suffix=alignment.fasta',
'--job=example'), outdir = wd)
#> PASTA INFO: Reading input sequences from 'example_seq.fasta'...
#> PASTA INFO: Configuration written to "/working_dir/example_temp_pasta_config.txt".
#>
#> PASTA INFO: Directory for temporary files created at /root/.pasta/example/tempab7o4zwo
#> PASTA INFO: Name translation information saved to /working_dir/example_temp_name_translation.txt as safe name, original name, blank line format.
#> PASTA INFO: Creating a starting tree for the PASTA algorithm...
#> PASTA INFO: Performing initial alignment of the entire data matrix...
#> PASTA INFO: Performing initial tree search to get starting tree...
#> PASTA INFO: Starting PASTA algorithm on initial tree...
#> PASTA INFO: Max subproblem set to 5
#> PASTA INFO: Step 0. Realigning with decomposition strategy set to mincluster
#> PASTA INFO: Step 0. Alignment obtained. Tree inference beginning...
#> PASTA INFO: realignment accepted and score improved.
#> PASTA INFO: current score: -21536.292, best score: -21536.292
#> PASTA INFO: TreeShrink option has been turned off!
#> PASTA INFO: Step 1. Realigning with decomposition strategy set to mincluster
#> PASTA INFO: Step 1. Alignment obtained. Tree inference beginning...
#> PASTA INFO: realignment accepted despite the score not improving.
#> PASTA INFO: current score: -21478.217, best score: -21478.217
#> PASTA INFO: TreeShrink option has been turned off!
#> PASTA INFO: Step 2. Realigning with decomposition strategy set to mincluster
#> PASTA INFO: Step 2. Alignment obtained. Tree inference beginning...
#> PASTA INFO: realignment accepted despite the score not improving.
#> PASTA INFO: current score: -21478.217, best score: -21478.217
#> PASTA INFO: TreeShrink option has been turned off!
#> PASTA INFO: Writing resulting alignment to /working_dir/example.alignment.fasta
#> PASTA INFO: Writing resulting tree to /working_dir/example.tre
#> PASTA INFO: Writing resulting likelihood score to /working_dir/example.score.txt
#> PASTA INFO: The resulting alignment (with the names in a "safe" form) was first written as the file "/working_dir/example_temp_iteration_2_seq_alignment.txt"
#> PASTA INFO: The resulting tree (with the names in a "safe" form) was first written as the file "/working_dir/example_temp_iteration_2_tree.tre"
#> PASTA INFO: Total time spent: 20.288654565811157s
# Verify results
list.files(wd)
#> [1] "example_seq.fasta"
#> [2] "example_temp_iteration_0_seq_alignment.txt"
#> [3] "example_temp_iteration_0_seq_unmasked_alignment.gz"
#> [4] "example_temp_iteration_0_tree.tre"
#> [5] "example_temp_iteration_1_seq_alignment.txt"
#> [6] "example_temp_iteration_1_seq_unmasked_alignment.gz"
#> [7] "example_temp_iteration_1_tree.tre"
#> [8] "example_temp_iteration_2_seq_alignment.txt"
#> [9] "example_temp_iteration_2_seq_unmasked_alignment.gz"
#> [10] "example_temp_iteration_2_tree.tre"
#> [11] "example_temp_iteration_initialsearch_seq_alignment.txt"
#> [12] "example_temp_iteration_initialsearch_seq_unmasked_alignment.gz"
#> [13] "example_temp_iteration_initialsearch_tree.tre"
#> [14] "example_temp_name_translation.txt"
#> [15] "example_temp_pasta_config.txt"
#> [16] "example.alignment.fasta"
#> [17] "example.err.txt"
#> [18] "example.out.txt"
#> [19] "example.score.txt"
#> [20] "example.tre"
The final alignment is contained within the “example.alignment.fasta”
file.
Key arguments
All PASTA arguments can be provided to the arglist as a character
vector. Below is a table describing some of the most common. All
arguments can be displayed using the -h
flag.
| Argument | Usage | Description |
| ---------------- | ------------------------ | --------------------------------------------------- |
| i | -i file | Specify input sequence file |
| t | -t file | Specify starting tree file |
| d | -d type | Specify sequence type (protein, RNA, DNA) |
| alignment suffix | –alignment-suffix=name | Specify the word ending for the resulting alignment |
| job | –job=name | Specify a name for the job |
In addition to the arguments provided in the arglist a user can
provide an outdir specifying the file location of where all resulting
PASTA analysis files should be returned.
Links
Find out more by visiting PASTA’s
homepage.
Please cite
- 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.
.
- Bennett et al. (2020). outsider: Install and run programs, outside
of R, inside of R. Journal of Open Source Software, In
review
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Learn more at outsider
website. Want to build your
own module? Check out outsider.devtools
website.
DomBennett/om..pasta documentation built on Jan. 17, 2020, 12:25 a.m.
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Run pasta with outsider in R
pasta (Practical Alignment using SATe and Transitivity): Multiple sequence alignment of biological sequences.
Install and look up help
library(outsider)
#> ----------------
#> outsider v 0.1.0
#> ----------------
#> - Security notice: be sure of which modules you install
module_install(repo = "dombennett/om..pasta")
#> -----------------------------------------------------
#> Warning: You are about to install an outsider module!
#> -----------------------------------------------------
#> Outsider modules install and run external programs
#> via Docker <https://www.docker.com>. These external
#> programs may communicate with the internet and could
#> potentially be malicious.
#>
#> Be sure to know the module you are about to install:
#> Is it from a trusted developer? Are colleagues using
#> it? Is it supposed to download lots of data? Is it
#> well used (e.g. check number of stars on GitHub)?
#> -----------------------------------------------------
#> Module information
#> -----------------------------------------------------
#> program: pasta
#> details: PASTA (Practical Alignment using Sate and TrAnsitivity) algorithm.
#> docker: dombennett
#> github: dombennett
#> url: https://github.com/dombennett/om..pasta
#> image: dombennett/om_pasta
#> container: om_pasta
#> package: om..pasta
#> Travis CI: Passing
#> -----------------------------------------------------
#> Enter any key to continue or press Esc to quit
#module_help(repo = "dombennett/om..pasta")
Aligning a small set of DNA sequences
The below example is adapted from the PASTA tutorial.
library(outsider)
# import
pasta <- module_import('pasta', repo = 'dombennett/om..pasta')
# get help
pasta('-h')
#> Usage: run_pasta.py [options] <settings_file1> <settings_file2> ...
#>
#>
#> PASTA performs iterative realignment and tree inference, similar to SATe, but
#> uses a very different merge algorithm which improves running time, memory
#> usage, and accuracy. The current code is heavily based on SATe, with lots of
#> modifications, many related to algorithmic differences between PASTA and SATe,
#> but also many scalability improvements (parallelization, tree parsing,
#> defaults, etc.)
#>
#> Minimally you must provide a sequence file (with the '--input' option); a
#> starting tree is optional. By default, important algorithmic parameters are
#> set based on automatic rules.
#>
#> The command line allows you to alter the behavior of the algorithm
#> (termination criteria, when the algorithm switches to "Blind" acceptance of
#> new alignments, how the tree is decomposed to find subproblems to be used, and
#> the external tools to use).
#>
#> 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.
#>
#> 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 that the use of --auto option can overwrite some
#> of the other options provided by commandline or through configuration files.
#>
#>
#> Options:
#> --version show program's version number and exit
#> -h, --help show this help message and exit
#>
#> commandline options:
#> -a, --aligned If used, then the input file be will treated as
#> aligned for the purposes of the first round of tree
#> inference (the algorithm will start with tree
#> searching on the input before re-aligning). This
#> option only applies if a starting tree is NOT given.
#> --alignment-suffix=ALIGNMENT-SUFFIX
#> suffix for alignment name (default: .marker001.[input
#> name].aln)
#> --auto This option is mostly for backward compatibility. If
#> used, then automatically identified default values for
#> the max_subproblem_size, number of cpus, tools,
#> breaking strategy, masking criteria, and stopping
#> criteria will be used. This is just like using the
#> default options. However, [WARNING] when auto option
#> is used PASTA overrides the value of these options
#> even if you have supplied them; we recommend that you
#> run this option with --exportconfig to see the exact
#> set of options that will be used in your analysis.
#> -d DATATYPE, --datatype=DATATYPE
#> Specify DNA, RNA, or Protein to indicate what type of
#> data is specified. Note that this option is NOT
#> automatically determined [default: dna]
#> --exportconfig=EXPORTCONFIG
#> Export the configuration to the specified file and
#> exit. This is useful if you want to combine several
#> configurations and command line settings into a single
#> configuration file to be used in other analyses.
#> -i INPUT, --input=INPUT
#> input sequence file
#> -j JOB, --job=JOB job name [pastajob]
#> --keepalignmenttemps
#> Keep even the realignment temporary running files
#> (this only has an effect if keeptemp is also
#> selected).
#> -k, --keeptemp Keep temporary running files? [default: disabled]
#> --missing=MISSING How to deal with missing data symbols. Specify either
#> "Ambiguous" or "Absent" if the input data contains
#> ?-symbols
#> -m, --multilocus Analyze multi-locus data? NOT SUPPORTED IN CURRENT
#> PASTA version.
#> --raxml-search-after
#> If used, the completion of the PASTA algorithm will be
#> followed by a tree search using RAxML on the masked
#> alignment. This can be useful if a very fast and
#> approximate tree estimator is used during the PASTA
#> algorithm. [default: disabled]
#> --temporaries=TEMPORARIES
#> directory that will be the parent for this job's
#> temporary file [default in PASTA home]
#> --timesfile=TIMESFILE
#> optional file that will store the times of events
#> during the PASTA run. If the file exists, new lines
#> will be
#> -t TREEFILE, --treefile=TREEFILE
#> starting tree file
#> --two-phase If used, then the program will not perform the PASTA
#> algorithm. Instead it will simply call the sequence
#> aligner to align the entire dataset then will call the
#> tree estimator to obtain the tree.
#> --untrusted If used, then the data in the input file will be
#> parsed using a more careful procedure. This will
#> generate more helpful error messages, but will use
#> more memory and be much slower for large inputs. If
#> this option is omitted, the error messages resulting
#> from invalid input data will be more cryptic.
#>
#> SATe acceptance options:
#> --blind-after-iter-without-imp=#
#> Maximum number of iterations without an improvement in
#> likelihood score that PASTA will run before switching
#> to blind mode. [default: disabled]
#> --blind-after-time-without-imp=#.#
#> Maximum time (in seconds) that PASTA will run without
#> an improvement in likelihood score before switching to
#> blind mode. [default: disabled]
#> --blind-after-total-iter=#
#> Maximum number of iterations that PASTA will run
#> before switching to blind mode. [default: 0]
#> --blind-after-total-time=#.#
#> Maximum time (in seconds) that PASTA will run before
#> switching to blind mode. [default: disabled]
#> --no-blind-mode-is-final
#> When the blind mode is final, then PASTA will never
#> leave blind mode once it is has entered blind mode.
#> --move-to-blind-on-worse-score
#> If True then PASTA will move to the blind mode as soon
#> it encounters a tree/alignment pair with a worse
#> score. This is essentially the same as running in
#> blind mode from the beginning, but it does allow one
#> to terminate a run at an interval from the first time
#> the algorithm fails to improve the score.
#>
#> SATe decomposition options:
#> --break-strategy=BREAK_STRATEGY
#> The method for choosing an edge when bisecting the
#> tree during decomposition [default: mincluster]
#> --max-subproblem-frac=#.#
#> The maximum size (number of leaves) of subproblems
#> specified in terms as a proportion of the total number
#> of leaves. When a subproblem contains this number of
#> leaves (or fewer), then it will not be decomposed
#> further. [default: automatically picked based on
#> alignment size]
#> --max-subproblem-size=#
#> The maximum size (number of leaves) of subproblems.
#> When a subproblem contains this number of leaves (or
#> fewer), then it will not be decomposed further.
#> [default: automatically picked based on alignment
#> size]
#> --max-subtree-diameter=#.#
#> The maximum diameter of each subtree. [default: 2.5]
#> --min-subproblem-size=#
#> The minimum size (number of leaves) of subproblems.
#> [default: 0]
#>
#> SATe filtering options:
#> --treeshrink-filter
#> If used, then the inferred FastTree will be filtered
#> by TreeShrink for long branch outliers.
#>
#> SATe output options:
#> -o OUTPUT_DIRECTORY, --output-directory=OUTPUT_DIRECTORY
#> directory for output files (defaults to input file
#> directory)
#> --no-return-final-tree-and-alignment
#> Return the best likelihood tree and alignment pair
#> instead of those from the last iteration; this is
#> discouraged with masking option enabled.
#>
#> SATe platform options:
#> --max-mem-mb=# The maximum memory available to OPAL (for the Java
#> heap size when running Java tools).
#> --num-cpus=# The number of processing cores that you would like to
#> assign to PASTA. This number should not exceed the
#> number of cores on your machine. [default: number of
#> cores available on the machine]
#>
#> SATe searching options:
#> --mask-gappy-sites=#
#> The minimum number of non-gap characters required in
#> each column passed to the tree estimation step.
#> Columns with fewer non-gap characters than the given
#> threshold will be masked out before passing the
#> alignment into the tree estimation module. These
#> columns will be present in the final alignment.
#> [default: 0.1% of alignment size]
#> --start-tree-search-from-current
#> If selected that the tree from the previous iteration
#> will be given to the tree searching tool as a starting
#> tree.
#>
#> SATe spaning-tree options:
#> --build-MST Construct the spanning tree using minimum spanning
#> tree algorithm [default: False]
#>
#> SATe termination options:
#> --after-blind-iter-term-limit=#
#> The maximum number of iteration that the PASTA
#> algorithm will run after PASTA has entered blind mode.
#> If the number is less than 1, then no iteration limit
#> will be used. [default: disabled]
#> --after-blind-iter-without-imp-limit=#
#> The maximum number of iterations without an
#> improvement in score that the PASTA algorithm will run
#> after entering BLIND mode. If the number is less than
#> 1, then no iteration limit will be used. [default:
#> disabled]
#> --after-blind-time-term-limit=#.#
#> Maximum time (in seconds) that PASTA will continue
#> starting new iterations of realigning and tree
#> searching after PASTA has entered blind mode. If the
#> number is less than 0, then no time limit will be
#> used. [default: disabled]
#> --after-blind-time-without-imp-limit=#.#
#> Maximum time (in seconds) since the last improvement
#> in score that PASTA will continue starting new
#> iterations of realigning and tree searching after
#> entering BLIND mode. If the number is less than 0,
#> then no time limit will be used. [default: disabled]
#> --iter-limit=# The maximum number of iteration that the PASTA
#> algorithm will run. If the number is less than 1,
#> then no iteration limit will be used. [default: 3]
#> --iter-without-imp-limit=#
#> The maximum number of iterations without an
#> improvement in score that the PASTA algorithm will
#> run. If the number is less than 1, then no iteration
#> limit will be used. [default: disabled]
#> --time-limit=#.# Maximum time (in seconds) that PASTA will continue
#> starting new iterations of realigning and tree
#> searching. If the number is less than 0, then no time
#> limit will be used. [default: disabled]
#> --time-without-imp-limit=#.#
#> Maximum time (in seconds) since the last improvement
#> in score that PASTA will continue starting new
#> iterations of realigning and tree searching. If the
#> number is less than 0, then no time limit will be
#> used. [default: disabled]
#>
#> SATe tools options:
#> --aligner=ALIGNER The name of the alignment program to use for
#> subproblems. [default: mafft]
#> --merger=MERGER The name of the alignment program to use to merge
#> subproblems. [default: OPAL]
#> --tree-estimator=TREE_ESTIMATOR
#> The name of the tree inference program to use to find
#> trees on fixed alignments. [default: fasttree]
# download
wd <- file.path(tempdir(), 'example_job')
if (!dir.exists(wd)) {
dir.create(wd)
}
# example DNA, based on MAFFT example
seq_file <- file.path(wd, 'example_seq.fasta')
url <- 'https://raw.githubusercontent.com/DomBennett/om..pasta/master/example_seq.fasta'
download.file(url = url, destfile = seq_file)
# run DNA alignment
pasta(arglist = c('-i', seq_file, '-d', 'dna',
'--alignment-suffix=alignment.fasta',
'--job=example'), outdir = wd)
#> PASTA INFO: Reading input sequences from 'example_seq.fasta'...
#> PASTA INFO: Configuration written to "/working_dir/example_temp_pasta_config.txt".
#>
#> PASTA INFO: Directory for temporary files created at /root/.pasta/example/tempab7o4zwo
#> PASTA INFO: Name translation information saved to /working_dir/example_temp_name_translation.txt as safe name, original name, blank line format.
#> PASTA INFO: Creating a starting tree for the PASTA algorithm...
#> PASTA INFO: Performing initial alignment of the entire data matrix...
#> PASTA INFO: Performing initial tree search to get starting tree...
#> PASTA INFO: Starting PASTA algorithm on initial tree...
#> PASTA INFO: Max subproblem set to 5
#> PASTA INFO: Step 0. Realigning with decomposition strategy set to mincluster
#> PASTA INFO: Step 0. Alignment obtained. Tree inference beginning...
#> PASTA INFO: realignment accepted and score improved.
#> PASTA INFO: current score: -21536.292, best score: -21536.292
#> PASTA INFO: TreeShrink option has been turned off!
#> PASTA INFO: Step 1. Realigning with decomposition strategy set to mincluster
#> PASTA INFO: Step 1. Alignment obtained. Tree inference beginning...
#> PASTA INFO: realignment accepted despite the score not improving.
#> PASTA INFO: current score: -21478.217, best score: -21478.217
#> PASTA INFO: TreeShrink option has been turned off!
#> PASTA INFO: Step 2. Realigning with decomposition strategy set to mincluster
#> PASTA INFO: Step 2. Alignment obtained. Tree inference beginning...
#> PASTA INFO: realignment accepted despite the score not improving.
#> PASTA INFO: current score: -21478.217, best score: -21478.217
#> PASTA INFO: TreeShrink option has been turned off!
#> PASTA INFO: Writing resulting alignment to /working_dir/example.alignment.fasta
#> PASTA INFO: Writing resulting tree to /working_dir/example.tre
#> PASTA INFO: Writing resulting likelihood score to /working_dir/example.score.txt
#> PASTA INFO: The resulting alignment (with the names in a "safe" form) was first written as the file "/working_dir/example_temp_iteration_2_seq_alignment.txt"
#> PASTA INFO: The resulting tree (with the names in a "safe" form) was first written as the file "/working_dir/example_temp_iteration_2_tree.tre"
#> PASTA INFO: Total time spent: 20.288654565811157s
# Verify results
list.files(wd)
#> [1] "example_seq.fasta"
#> [2] "example_temp_iteration_0_seq_alignment.txt"
#> [3] "example_temp_iteration_0_seq_unmasked_alignment.gz"
#> [4] "example_temp_iteration_0_tree.tre"
#> [5] "example_temp_iteration_1_seq_alignment.txt"
#> [6] "example_temp_iteration_1_seq_unmasked_alignment.gz"
#> [7] "example_temp_iteration_1_tree.tre"
#> [8] "example_temp_iteration_2_seq_alignment.txt"
#> [9] "example_temp_iteration_2_seq_unmasked_alignment.gz"
#> [10] "example_temp_iteration_2_tree.tre"
#> [11] "example_temp_iteration_initialsearch_seq_alignment.txt"
#> [12] "example_temp_iteration_initialsearch_seq_unmasked_alignment.gz"
#> [13] "example_temp_iteration_initialsearch_tree.tre"
#> [14] "example_temp_name_translation.txt"
#> [15] "example_temp_pasta_config.txt"
#> [16] "example.alignment.fasta"
#> [17] "example.err.txt"
#> [18] "example.out.txt"
#> [19] "example.score.txt"
#> [20] "example.tre"
The final alignment is contained within the “example.alignment.fasta” file.
Key arguments
All PASTA arguments can be provided to the arglist as a character
vector. Below is a table describing some of the most common. All
arguments can be displayed using the -h
flag.
| Argument | Usage | Description |
| ---------------- | ------------------------ | --------------------------------------------------- |
| i | -i file | Specify input sequence file |
| t | -t file | Specify starting tree file |
| d | -d type | Specify sequence type (protein, RNA, DNA) |
| alignment suffix | –alignment-suffix=name | Specify the word ending for the resulting alignment |
| job | –job=name | Specify a name for the job |
In addition to the arguments provided in the arglist a user can
provide an outdir specifying the file location of where all resulting
PASTA analysis files should be returned.
Links
Find out more by visiting PASTA’s homepage.
Please cite
- 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. .
- Bennett et al. (2020). outsider: Install and run programs, outside of R, inside of R. Journal of Open Source Software, In review
An outsider module
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