Abstract
Motivation: Multiple sequence alignments (MSAs) with large numbers of sequences are now commonplace. However, current multiple alignment benchmarks are ill-suited for testing these types of alignments, as test cases either contain a very small number of sequences or are based purely on simulation rather than empirical data. Results: We take advantage of recent developments in protein structure prediction methods to create a benchmark (ContTest) for protein MSAs containing many thousands of sequences in each test case and which is based on empirical biological data. We rank popular MSA methods using this benchmark and verify a recent result showing that chained guide trees increase the accuracy of progressive alignment packages on datasets with thousands of proteins. Availability and implementation: Benchmark data and scripts are available for download at http://www.bioinf.ucd.ie/download/ContTest.tar.gz. Contact: des.higgins@ucd.ie Supplementary information: Supplementary data are available at Bioinformatics online.
Highlights
Making a multiple sequence alignment (MSA) of nucleotide or amino acid sequences is a crucial step needed in a wide variety of bioinformatics studies
We developed ContTest, a benchmark for large protein MSAs based on the accuracy of de novo contact map prediction
The Pfam database contains MSAs of all sequences in each protein family, and we used the benchmark to score the full alignments from Pfam 27
Summary
Making a multiple sequence alignment (MSA) of nucleotide or amino acid sequences is a crucial step needed in a wide variety of bioinformatics studies. Structure- and phylogeny-based benchmarks, in which scores are based on structural superpositions and accurate inference of phylogenetic trees, respectively, are strongly grounded in empirical biological data, but they focus on alignments of small numbers of sequences and are difficult to scale to larger datasets. Simulation- and consistency-based benchmarks are based on simulations of protein evolution and simple agreement between different MSA methods, respectively, and can involve alignments of arbitrary size. It is unclear, how well simulated sequences model actual biological sequences, while consistency measures only how similar the results of one heuristic method are to the results of other heuristic methods
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