T-Coffee: A novel method for fast and accurate multiple sequence alignment

We describe a new method (T-Coffee) for multiple sequence alignment that pr ovides a dramatic improvement in accuracy with a modest sacrifice in speed as compared to the most commonly used alternatives. The method is broadly b ased on the popular progressive approach to multiple alignment but avoids t he most serious pitfalls caused by the greedy nature of this algorithm. Wit h T-Coffee we pre-process a data set of all pair-wise alignments between th e sequences. This provides us with a library of alignment information that can be used to guide the progressive alignment. Intermediate alignments are then based not only on the sequences to be aligned next but also on how al l of the sequences align with each other. This alignment information can be derived from heterogeneous sources such as a mixture of alignment programs and/or structure superposition. Here, we illustrate the power of the appro ach by using a combination of local and global pair-wise alignments to gene rate the library. The resulting alignments are significantly more reliable, as determined by comparison with a set of 141 test cases, than any of the popular alternatives that we tried. The improvement, especially clear with the more difficult test cases, is always visible, regardless of the phyloge netic spread of the sequences in the tests. (C) 2000 Academic Press.