Research at the Higgins Lab,
University College Dublin

Clustal (

Our lab maintains and develops the Clustal Omega, Clustal W and Clustal X packages for multiple sequence alignment in collaboration with the groups of Toby Gibson at EMBL (, Julie Thompson in Strasbourg ( and Rodrigo Lopez at the EBI ( The package can be downloaded from the Clustal homepage ( or from the EBI or run on-line (

The package was recently revised and we released version 2.0 in Sept. 2007 (Larkin, et al, 2007). We are currently working on version 3.0 which we hope to release by 2010. The new work is funded by Science Foundation Ireland ( and will involve improving the accuracy of the alignments and the capacity to align very large data sets.


Multiple Sequence Alignment with Clustal Omega

The latest program of the Clustal family of multiple sequence aligners is Clustal Omega (Fabian Sievers, Andreas Wilm et al, 2011). It offers a significant increase in scalability over previous versions, allowing hundreds of thousands of sequences to be aligned in only a few hours. It will also make use of multiple processors, where present. In addition, the quality of alignments is superior to previous versions, as measured by a range of popular benchmarks. Please note that Clustal Omega is currently a command line-only tool.


T-Coffee ( was developed by and is maintained by Cedric Notredame ( ). It features a powerful and flexible approach to merging data from different sources to make high accuracy multiple sequence alignments of protein or nucleotide sequences. Our laboratory, collaborates with Cedric in the implementation and testing of T-Coffee for RNA alignment (R-Coffee, Wilm et al, 2008), protein structural alignments (3D-Coffee, O’ Sullivan, et al, 2003) and the merging of many multiple alignments (M-Coffee, Wallace, et al, 2006).

Multivariate Analysis of Omics Data

We have been applying a range of multivariate analysis methods to analyse high-dimensional genomics related datasets for some years. This work was initiated by Aedin Culhane ( in our lab (now in the Dana Faber, in Boston) and with Guy Perriere (, Lyons, France, as collaborator. All of these data sets have a problem in that they usually have considerably more variables than cases and require careful selection of methods. In particular, we have been using Correspondence Analysis, Between Groups Analysis and Co-Inertia analysis and using the ADE4 R ( ) package of Jean Thiolouse (, in Lyons, France to apply these. ADE4 is free and has a huge range of clustering, ordination and discriminant methods.
We have applied these methods to e.g.
Sequence alignments (Wallace, et al, 2007)
Promoter motifs and gene expression data (Jeffery, et al, 2007)
Proteomics and gene expression data (Fagan, et al, 2007)
Cross platform gene expression data analysis (Culhane, et al, 2003)


Effect of Guidetrees, Tree Balance and Phylogeny on Multiple Sequence Alignment Quality

A systematic exploration of the effect of guide-tree topology on alignment quality for up to 8 sequences (and to a limited degree for 16 sequences) can be found in Fabian Sievers et al, BMC Bioinformatics, October 2014, 15:338. There the Supplement contains a list of all rooted, toplologically distict, unlabeled, bifurcating trees with up to 8 sequences. The number of different rooted, toplologically distict, unlabeled, bifurcating trees is given by the Wedderburn-Etherington numbers. For 2 and 3 leaves there is only one possible tree, for 4 sequences there are 2 possible trees, for 5 there are 3, for 6 there are 6, for 7 there are 11 and for 8 leaves there are 23 unlabeled binary rooted trees. Tree shape can be summarised by the degree of tree balance or imbalance. Some measures of tree im/balance are defined in Shao, K., Sokal, R.: Tree balance. Systematic Zoology 39 (3), 266-276 (1990). Values for Tree Depth, Sackin's measure, Colless' measure, Sokal's inv-max measure, Shannon Entropy and Tree Diameter are given for up to 8 sequences in the Supplement. A more complete list for up to 16 sequences can be found in the list of all topologically distinct trees with up to 16 leaves. This list also contains values for the rescaled Sackin and Colless measures, the number of sub-trees made up of exactly 2 leaves (cherries), the length of the longest completely imbalanced/chained sub-tree (caterpillar) and the number of symmetries (a,b) ⇔ (b,a), where a and b can be either leaves or sub-trees themselves.
The expected values of the Sackin and the Colless measure under the Equal Rates Markov or Yule (Yule et al., 1925) model, and the uniform or Proportional to Distinguishable Arrangements model are shown in Fox et al, Bioinformatics (2015).
Boyce et al have shown that 'Simple chained guide trees give high-quality protein multiple sequence alignments', PNAS 2014 ; July 9, 2014. Chained guide-trees are the most imbalanced trees possible, where at each node at least one branch subtends exactly one leaf.