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PSAR: Measuring Multiple Sequence Alignment Reliability by Probabilistic Sampling

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Research in Computational Molecular Biology (RECOMB 2011)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6577))

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Introduction

Multiple sequence alignment (MSA), which is of fundamental importance for comparative genomics, is a difficult problem and error-prone. Therefore, it is essential to measure the reliability of the alignments and incorporate it into downstream analyses. Many studies have been conducted to find the extent, cause and effect of the alignment errors [4], and to heuristically estimate the quality of alignments without using the true alignment, which is unknown [2]. However, it is still unclear whether the heuristically chosen measures are general enough to take into account all alignment errors. In this paper, we present a new alignment reliability score, called PSAR (Probabilistic Sampling-based Alignment Reliability) score.

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References

  1. Durbin, R., Eddy, S.R., Krogh, A., Mitchison, G.: Biological sequence analysis: probabilistic models of proteins and nucleic acids. Cambridge University Press, Cambridge (1998)

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Author information

Authors and Affiliations

  1. Institute for Genomic Biology, University of Illinois, Urbana-Champaign, IL, 61801, U.S.A.

    Jaebum Kim & Jian Ma

  2. Department of Bioengineering, University of Illinois, Urbana-Champaign, IL, 61801, U.S.A.

    Jian Ma

Authors
  1. Jaebum Kim
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  2. Jian Ma
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Editors and Affiliations

  1. EBU3b, University of California San Diego, #4218, 9500 Gilman Drive, 92093-0404, La Jolla, CA, USA

    Vineet Bafna

  2. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby, BC, Canada

    S. Cenk Sahinalp

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© 2011 Springer-Verlag Berlin Heidelberg

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Kim, J., Ma, J. (2011). PSAR: Measuring Multiple Sequence Alignment Reliability by Probabilistic Sampling. In: Bafna, V., Sahinalp, S.C. (eds) Research in Computational Molecular Biology. RECOMB 2011. Lecture Notes in Computer Science(), vol 6577. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20036-6_14

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  • DOI: https://doi.org/10.1007/978-3-642-20036-6_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20035-9

  • Online ISBN: 978-3-642-20036-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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