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

Abstract

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 under GNU General Public License.

Phylogenomic analyses of thePhotiniacomplex support the recognition of a new genusPhippsiomelesand the resurrection of a redefinedStranvaesiain Maleae (Rosaceae)

“…To reduce the systematic errors produced by poor alignment, we used the trimAL v1.2 (Capella‐Gutiérrez et al, ) with a heuristic method to decide which is the best‐automated method to trim the alignment of the WP. All the 80 CDSs of each plastome were extracted separately by Geneious Prime; the alignment of each gene was concatenated by AMAS (Borowiec, ). Including 31 plastomes downloaded from NCBI, 81 plastomes were aligned by MAFFT v.7.409 (Nakamura et al, ) with default parameters.…”

A customized nuclear target enrichment approach for developing a phylogenomic baseline for Dioscorea yams (Dioscoreaceae)

“…We visually identified alignment blocks that differed between DNA‐based and transcriptome‐based sequences; these may result from post‐transcriptional modification processes, and so we deleted the divergent sections of transcriptome‐based sequences. We also obtained summary statistics on gene alignments using AMAS (Borowiec, ), including length, missing data, and number of parsimony informative sites (target gene summary statistics are available in the Dryad Digital Repository; Soto Gomez et al., ).…”

Phylogenomic Insights into Mouse Evolution Using a Pseudoreference Approach

“…To incorporate this variation, we extended each target by 200 bp on both ends and merged regions that were up to 1 kbp apart, increasing the total data set from 54.3 to 163.4 Mbp. As above, we first used RAxML (GTR + Γ, 200 bootstrap replicates) to estimate an ML tree per chromosome by extracting extended targets using bedtools v2.2.5 and combining regions with AMAS (Borowiec 2016). For these data, no alignment is required because indel variation is not incorporated into the pseudoreference.…”