Using de novo protein structure predictions to measure the quality of very large multiple sequence alignments.
Where this comes from
- Record sourced from PubMed, PMID 26568625.
- Also identified by DOI 10.1093/bioinformatics/btv592 and PMC identifier 5939968.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
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. 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. Benchmark data and scripts are available for download at http://www.bioinf.ucd.ie/download/ContTest.tar.gz des.higgins@ucd.ie Supplementary data are available at Bioinformatics online.
Medical subject headings
- Sequence Alignment