Nucleic Acids Research, 2007, Vol. 35, Web Server issue W645–W648 doi:10.1093/nar/gkm333 The M-Coffee web server: a meta-method for computing multiple sequence alignments by combining alternative alignment methods Sebastien Moretti1, Fabrice Armougom3, Iain M. Wallace 2 , Desmond G. Higgins 2 , Cornelius V. Jongeneel1 and Cedric Notredame3,* 1Swiss Institute of Bioinformatics, Baˆ timent Ge´ nopode, UNIL, CH-101 Lausanne, 2Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland and 3Information Ge´ nomique et Structurale, CNRS UPR2589, Institute for Structural Biology and Microbiology (IBSM), Parc Scientifique de Luminy, 163 Avenue de Luminy, FR- 13288, Marseille cedex 09, France Received January 31, 2007; Revised April 15, 2007; Accepted April 18, 2007 ABSTRACT The M-Coffee server is a web server that makes it possible to compute multiple sequence alignments (MSAs) by running several MSA methods and combining their output into one single model. This allows the user to simultaneously run all his methods of choice without having to arbitrarily choose one of them. The MSA is delivered along with a local estimation of its consistency with the individual MSAs it was derived from. The computa- tion of the consensus multiple alignment is carried out using a special mode of the T-Coffee package [Notredame, Higgins and Heringa (T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 2000; 302: 205–217); Wallace, O’Sullivan, Higgins and Notredame (M-Coffee: com- bining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res. 2006; 34: 1692–1699)] Given a set of sequences (DNA or proteins) in FASTA format, M-Coffee delivers a multiple alignment in the most common formats. M-Coffee is a freeware open source package distributed under a GPL license and it is available either as a standalone package or as a web service from www.tcoffee.org. INTRODUCTION The computation of an accurate multiple sequence alignment (MSA) is central to a large number of bioinformatics analyses, ranging from phylogeny, proﬁle construction, structure prediction and more recently sequence/structure activity relationship. Despite its impor- tance, the MSA problem has not yet met with a deﬁnitive answer and a wide variety of alternative methods are currently available (3,4). All these methods are meant to address the same problem in diﬀerent ways. In recent years, many eﬀorts have been undertaken to characterize their relative accuracy but the overall outcome suggests that there is no such thing as a perfect MSA method, with each individual method having speciﬁc strengths and weaknesses. In practice, evaluation is made using struc- ture-based MSAs as a standard of truth and the expected accuracy of a method is deduced from its ability to produce a structurally correct sequence alignment while using sequence information only. At least ﬁve such collections of reference alignments (5–8) have been established, and although some methods give better average results than others, one cannot know in advance which method will outperform the others on a given dataset. As such, it is always possible for the worst method to outperform all the others on a speciﬁc dataset. For the biologist, this makes it impossible to use anything other than a weak statistical argument (i.e. best method on average) to choose one method among the others when computing an alignment. The design of meta-methods (or jury-based methods) is one way of addressing such situations in biology. Meta- methods are meant to combine the output of several alternative methods into one ﬁnal output. They are based on the empirical reasoning that errors produced by independent prediction systems should not be consistent, therefore suggesting agreement as an indication of correctness. Such an approach was successfully used in the ﬁeld of gene predictions (9) or for secondary structure predictions (10). Combining alignments, however, is less simple than building consensus prediction and it is only in 1999 that an eﬀective strategy was proposed by Bucka- Lassen (11). An alternative to the Bucka-Lassen strategy, using consistency, was later introduced in the T-Coﬀee (1) algorithm. Recently, this algorithm was further modiﬁed in order to address the problem of combining alternative MSAs into one (2). T-Coﬀee (1) is a progressive consistency-based algorithm that compiles an alignment *To whom correspondence should be addressed. Tel: þ33 491 106 486; Fax: þ33 491 106 489; Email: cedric.notredame@europe.com 2007 The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.