Journal
JOURNAL OF COMPUTATIONAL BIOLOGY
Volume 22, Issue 5, Pages 377-386Publisher
MARY ANN LIEBERT, INC
DOI: 10.1089/cmb.2014.0156
Keywords
metagenomics; phylogenetic trees; molecular evolution; algorithms; multiple alignment
Categories
Funding
- National Science Foundation (NSF) [DBI 0733029]
- Howard Hughes Medical Institute (HHMI) International Predoctoral Fellowship
- University of Alberta
- iPlant Collaborative, NSF [DBI-1265383]
- NSF [0331453]
- National Institutes of Health (NIH) [T32-HG000046, NIA U24-AG041689, R01-GM099962]
- Health Research Formula Fund from the Pennsylvania Department of Health
- Emerging Frontiers
- Direct For Biological Sciences [0331453] Funding Source: National Science Foundation
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We introduce PASTA, a new multiple sequence alignment algorithm. PASTA uses a new technique to produce an alignment given a guide tree that enables it to be both highly scalable and very accurate. We present a study on biological and simulated data with up to 200,000 sequences, showing that PASTA produces highly accurate alignments, improving on the accuracy and scalability of the leading alignment methods (including SATe). We also show that trees estimated on PASTA alignments are highly accurate-slightly better than SATe trees, but with substantial improvements relative to other methods. Finally, PASTA is faster than SATe, highly parallelizable, and requires relatively little memory.
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