title: ReformAlign: improved multiple sequence alignments using a profile-based meta-alignment approach.
abstract: BACKGROUND
  Obtaining an accurate sequence alignment is fundamental for consistently analyzing biological data. Although this problem may be efficiently solved when only two sequences are considered, the exact inference of the optimal alignment easily gets computationally intractable for the multiple sequence alignment case. To cope with the high computational expenses, approximate heuristic methods have been proposed that address the problem indirectly by progressively aligning the sequences in pairs according to their relatedness. These methods however are not flexible to change the alignment of an already aligned group of sequences in the view of new data, resulting thus in compromises on the quality of the deriving alignment. In this paper we present ReformAlign, a novel meta-alignment approach that may significantly improve on the quality of the deriving alignments from popular aligners. We call ReformAlign a meta-aligner as it requires an initial alignment, for which a variety of alignment programs can be used. The main idea behind ReformAlign is quite straightforward: at first, an existing alignment is used to construct a standard profile which summarizes the initial alignment and then all sequences are individually re-aligned against the formed profile. From each sequence-profile comparison, the alignment of each sequence against the profile is recorded and the final alignment is indirectly inferred by merging all the individual sub-alignments into a unified set. The employment of ReformAlign may often result in alignments which are significantly more accurate than the starting alignments.
  
  
  RESULTS
  We evaluated the effect of ReformAlign on the generated alignments from ten leading alignment methods using real data of variable size and sequence identity. The experimental results suggest that the proposed meta-aligner approach may often lead to statistically significant more accurate alignments. Furthermore, we show that ReformAlign results in more substantial improvement in cases where the starting alignment is of relatively inferior quality or when the input sequences are harder to align.
  
  
  CONCLUSIONS
  The proposed profile-based meta-alignment approach seems to be a promising and computationally efficient method that can be combined with practically all popular alignment methods and may lead to significant improvements in the generated alignments.
authors.affiliation: Faculty of Biology, Department II, Ludwig-Maximilians Universität München, Planegg-Martinsried 82152, Germany. lyras@biologie.uni-muenchen.de.
authors.forename: Dimitrios P
authors.initials: DP
authors.lastname: Lyras
authors.forename: Dirk
authors.initials: D
authors.lastname: Metzler
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D011786:Quality Control; D016415:Sequence Alignment / Q000379:methods*; D012984:Software
references.citation: J Comput Biol. 1994 Winter;1(4):337-48
references.pmid: 8790475
references.citation: Mol Biol Evol. 2013 Apr;30(4):772-80
references.pmid: 23329690
references.citation: J Mol Biol. 2000 Sep 8;302(1):205-17
references.pmid: 10964570
references.citation: Pac Symp Biocomput. 2002;:115-26
references.pmid: 11928468
references.citation: Comput Appl Biosci. 1993 Jun;9(3):361-70
references.pmid: 8324637
references.citation: Nucleic Acids Res. 2010 Aug;38(15):4917-28
references.pmid: 20413579
references.citation: Bioinformatics. 2002 Feb;18(2):306-14
references.pmid: 11847078
references.citation: BMC Bioinformatics. 2004 Aug 19;5:113
references.pmid: 15318951
references.citation: Nucleic Acids Res. 2009 Feb;37(3):858-65
references.pmid: 19103665
references.citation: BMC Bioinformatics. 2011 May 10;12:144
references.pmid: 21569267
references.citation: Nucleic Acids Res. 2004 Mar 19;32(5):1792-7
references.pmid: 15034147
references.citation: Bioinformatics. 2007 Oct 1;23(19):2648-9
references.pmid: 17686799
references.citation: Bioinformatics. 2007 Nov 1;23(21):2947-8
references.pmid: 17846036
references.citation: Mol Syst Biol. 2011 Oct 11;7:539
references.pmid: 21988835
references.citation: Nucleic Acids Res. 2005 Apr 28;33(8):2433-9
references.pmid: 15860779
references.citation: Nucleic Acids Res. 1999 Jan 1;27(1):229-32
references.pmid: 9847187
references.citation: Bioinformatics. 2011 Dec 15;27(24):3356-63
references.pmid: 21998158
references.citation: BMC Bioinformatics. 2004 Sep 30;5:140
references.pmid: 15458580
references.citation: Proteins. 2005 Oct 1;61(1):127-36
references.pmid: 16044462
references.citation: PLoS Comput Biol. 2007 Aug;3(8):e123
references.pmid: 17784778
references.citation: Nucleic Acids Res. 1999 Jul 1;27(13):2682-90
references.pmid: 10373585
references.citation: Genome Res. 2005 Feb;15(2):330-40
references.pmid: 15687296
references.citation: J Mol Evol. 1984;20(2):175-86
references.pmid: 6433036
references.citation: Methods Mol Biol. 2008;484:379-413
references.pmid: 18592193
references.citation: J Comput Biol. 2001;8(6):615-23
references.pmid: 11747615
references.citation: Comput Appl Biosci. 1989 Apr;5(2):151-3
references.pmid: 2720464
references.citation: J Mol Biol. 1970 Mar;48(3):443-53
references.pmid: 5420325
references.citation: BMC Bioinformatics. 2010 Dec 17;11:601
references.pmid: 21167044
references.citation: Bioinformatics. 2012 Feb 15;28(4):495-502
references.pmid: 22199391
references.citation: Curr Opin Struct Biol. 2006 Jun;16(3):368-73
references.pmid: 16679011
references.citation: Nucleic Acids Res. 2008 May;36(9):e52
references.pmid: 18420654
references.citation: Algorithms Mol Biol. 2006 Oct 24;1:19
references.pmid: 17062125
references.citation: BMC Bioinformatics. 2009 Dec 02;10:396
references.pmid: 19954534
references.citation: Algorithms Mol Biol. 2008 May 27;3:6
references.pmid: 18505568
references.citation: J Mol Biol. 1987 Nov 20;198(2):327-37
references.pmid: 3430611
references.citation: Pharmacogenomics. 2002 Jan;3(1):131-44
references.pmid: 11966409
references.citation: BMC Bioinformatics. 2003 Oct 10;4:47
references.pmid: 14552658
references.citation: J Mol Evol. 1987;25(4):351-60
references.pmid: 3118049
references.citation: J Mol Biol. 1982 Dec 15;162(3):705-8
references.pmid: 7166760
references.citation: Proteins. 2000 Jul 1;40(1):6-22
references.pmid: 10813826
references.citation: Comput Appl Biosci. 1991 Oct;7(4):479-84
references.pmid: 1747779
references.citation: Proc Natl Acad Sci U S A. 1985 May;82(10):3073-7
references.pmid: 3858804
references.citation: Nucleic Acids Res. 1994 Nov 11;22(22):4673-80
references.pmid: 7984417