Abstract
Multiple sequence alignment (MSA) generally constitutes the foundation of many bioinformatics studies involving functional, structural, and evolutionary relationship analysis between sequences. As a result of the exponential computational complexity of the exact approach to producing optimal multiple alignments, the majority of state-of-the-art MSA algorithms are designed based on the progressive alignment heuristic. In this chapter, we outline MSAProbs, a parallelized MSA algorithm for protein sequences based on progressive alignment. To achieve high alignment accuracy, this algorithm employs a hybrid combination of a pair hidden Markov model and a partition function to calculate posterior probabilities. Furthermore, we provide some practical advice on the usage of the algorithm.
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References
Feng DF, Doolittle RF (1987) Progressive sequence alignment as a prerequisite to correct phylogenetic trees. J Mol Evol 25:351–361
Liu Y, Schmidt B, Maskell DL (2010) MSAProbs: multiple sequence alignment based on pair hidden Markov models and partition function posterior probabilities. Bioinformatics 26:1958–1964
Durbin R, Eddy SR, Krogh A, Mitchison G (1998) Biological sequence analysis: probabilistic models of proteins and nucleic acids. Cambridge University Press, Cambridge
Miyazawa S (1995) A reliable sequence alignment method based on probabilities of residue correspondences. Protein Eng 8:999–1009
Thompson JD, Koehl P, Ripp R, Poch O (2005) BAliBASE 3.0: latest developments of the multiple sequence alignment benchmark. Proteins 61:127–136
Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792–1797
Sievers F, Wilm A, Dineen D et al (2011) Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol 7:539
Chang JM, Di Tommaso P, Taly JF et al (2012) Accurate multiple sequence alignment of transmembrane proteins with PSI-Coffee. BMC Bioinformatics 13:S1
Deng X, Cheng J (2011) MSACompro: protein multiple sequence alignment using predicted secondary structure, solvent accessibility, and residue–residue contacts. BMC Bioinformatics 12:472
Vingron M, Argos P (1989) A fast and sensitive multiple sequence alignment algorithm. Comput Appl Biosci 5:115–121
Gotoh O (1990) Consistency of optimal sequence alignments. Bull Math Biol 52:509–525
Notredame C, Holm L, Higgins DG (1998) COFFEE: an objective function for multiple sequence alignments. Bioinformatics 14:407–422
Notredame C, Higgins DG, Heringa J (2000) T-coffee: a novel method for fast and accurate multiple sequence alignment. J Mol Biol 302:205–217
Do CB, Mahabhashyam MS, Brudno M et al (2005) ProbCons: probabilistic consistency-based multiple sequence alignment. Genome Res 15:330–340
Liu Y, Schmidt B, Maskell DL (2009) MSA-CUDA: multiple sequence alignment on graphics processing units with CUDA. 20th IEEE international conference on application-specific systems, architectures and processors, pp 121–128
Thompson JD, Higgins DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 22:4673–4680
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Liu, Y., Schmidt, B. (2014). Multiple Protein Sequence Alignment with MSAProbs. In: Russell, D. (eds) Multiple Sequence Alignment Methods. Methods in Molecular Biology, vol 1079. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-646-7_14
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DOI: https://doi.org/10.1007/978-1-62703-646-7_14
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Publisher Name: Humana Press, Totowa, NJ
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Online ISBN: 978-1-62703-646-7
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