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Multiple Sequence Alignment for Large Heterogeneous Datasets Using SATé, PASTA, and UPP

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Multiple Sequence Alignment

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2231))

Abstract

The estimation of very large multiple sequence alignments is a challenging problem that requires special techniques in order to achieve high accuracy. Here we describe two software packages—PASTA and UPP—for constructing alignments on large and ultra-large datasets. Both methods have been able to produce highly accurate alignments on 1,000,000 sequences, and trees computed on these alignments are also highly accurate. PASTA provides the best tree accuracy when the input sequences are all full-length, but UPP provides improved accuracy compared to PASTA and other methods when the input contains a large number of fragmentary sequences. Both methods are available in open source form on GitHub.

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Notes

  1. 1.

    This chapter is an update of [9], a previous article for Methods in Molecular Biology, which focused on using SATé [1, 2] for co-estimation of alignments and trees.

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Acknowledgements

This paper was supported by NSF grant ABI-1458652 to TW and NSF grant IIS-1845967 to SM.

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Authors and Affiliations

  1. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Tandy Warnow

  2. Electrical and Computer Engineering, University of California at San Diego, La Jolla, CA, USA

    Siavash Mirarab

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  1. Tandy Warnow
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  2. Siavash Mirarab
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Correspondence to Tandy Warnow .

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Editors and Affiliations

  1. Research Institute for Microbial Disease, Osaka University, Osaka, Japan

    Kazutaka Katoh

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Warnow, T., Mirarab, S. (2021). Multiple Sequence Alignment for Large Heterogeneous Datasets Using SATé, PASTA, and UPP. In: Katoh, K. (eds) Multiple Sequence Alignment. Methods in Molecular Biology, vol 2231. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1036-7_7

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  • DOI: https://doi.org/10.1007/978-1-0716-1036-7_7

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