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AMAS: a fast tool for alignment manipulation and computing of summary statistics

The amount of data used in phylogenetics has grown explosively in the recent years and many phylogenies are inferred with hundreds or even thousands of loci and many taxa. These modern phylogenomic studies often entail separate analyses of each of the loci in addition to multiple analyses of subsets...

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Autor principal: Borowiec, Marek L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4734057/
https://www.ncbi.nlm.nih.gov/pubmed/26835189
http://dx.doi.org/10.7717/peerj.1660
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author Borowiec, Marek L.
author_facet Borowiec, Marek L.
author_sort Borowiec, Marek L.
collection PubMed
description The amount of data used in phylogenetics has grown explosively in the recent years and many phylogenies are inferred with hundreds or even thousands of loci and many taxa. These modern phylogenomic studies often entail separate analyses of each of the loci in addition to multiple analyses of subsets of genes or concatenated sequences. Computationally efficient tools for handling and computing properties of thousands of single-locus or large concatenated alignments are needed. Here I present AMAS (Alignment Manipulation And Summary), a tool that can be used either as a stand-alone command-line utility or as a Python package. AMAS works on amino acid and nucleotide alignments and combines capabilities of sequence manipulation with a function that calculates basic statistics. The manipulation functions include conversions among popular formats, concatenation, extracting sites and splitting according to a pre-defined partitioning scheme, creation of replicate data sets, and removal of taxa. The statistics calculated include the number of taxa, alignment length, total count of matrix cells, overall number of undetermined characters, percent of missing data, AT and GC contents (for DNA alignments), count and proportion of variable sites, count and proportion of parsimony informative sites, and counts of all characters relevant for a nucleotide or amino acid alphabet. AMAS is particularly suitable for very large alignments with hundreds of taxa and thousands of loci. It is computationally efficient, utilizes parallel processing, and performs better at concatenation than other popular tools. AMAS is a Python 3 program that relies solely on Python’s core modules and needs no additional dependencies. AMAS source code and manual can be downloaded from http://github.com/marekborowiec/AMAS/ under GNU General Public License.
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spelling pubmed-47340572016-02-01 AMAS: a fast tool for alignment manipulation and computing of summary statistics Borowiec, Marek L. PeerJ Computational Biology The amount of data used in phylogenetics has grown explosively in the recent years and many phylogenies are inferred with hundreds or even thousands of loci and many taxa. These modern phylogenomic studies often entail separate analyses of each of the loci in addition to multiple analyses of subsets of genes or concatenated sequences. Computationally efficient tools for handling and computing properties of thousands of single-locus or large concatenated alignments are needed. Here I present AMAS (Alignment Manipulation And Summary), a tool that can be used either as a stand-alone command-line utility or as a Python package. AMAS works on amino acid and nucleotide alignments and combines capabilities of sequence manipulation with a function that calculates basic statistics. The manipulation functions include conversions among popular formats, concatenation, extracting sites and splitting according to a pre-defined partitioning scheme, creation of replicate data sets, and removal of taxa. The statistics calculated include the number of taxa, alignment length, total count of matrix cells, overall number of undetermined characters, percent of missing data, AT and GC contents (for DNA alignments), count and proportion of variable sites, count and proportion of parsimony informative sites, and counts of all characters relevant for a nucleotide or amino acid alphabet. AMAS is particularly suitable for very large alignments with hundreds of taxa and thousands of loci. It is computationally efficient, utilizes parallel processing, and performs better at concatenation than other popular tools. AMAS is a Python 3 program that relies solely on Python’s core modules and needs no additional dependencies. AMAS source code and manual can be downloaded from http://github.com/marekborowiec/AMAS/ under GNU General Public License. PeerJ Inc. 2016-01-28 /pmc/articles/PMC4734057/ /pubmed/26835189 http://dx.doi.org/10.7717/peerj.1660 Text en ©2016 Borowiec http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Computational Biology
Borowiec, Marek L.
AMAS: a fast tool for alignment manipulation and computing of summary statistics
title AMAS: a fast tool for alignment manipulation and computing of summary statistics
title_full AMAS: a fast tool for alignment manipulation and computing of summary statistics
title_fullStr AMAS: a fast tool for alignment manipulation and computing of summary statistics
title_full_unstemmed AMAS: a fast tool for alignment manipulation and computing of summary statistics
title_short AMAS: a fast tool for alignment manipulation and computing of summary statistics
title_sort amas: a fast tool for alignment manipulation and computing of summary statistics
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4734057/
https://www.ncbi.nlm.nih.gov/pubmed/26835189
http://dx.doi.org/10.7717/peerj.1660
work_keys_str_mv AT borowiecmarekl amasafasttoolforalignmentmanipulationandcomputingofsummarystatistics