The significance of each block is given a statistical value. The program has two different methods to search for blocks, the more accurate one is the Gibbs procedure. Evaluating local multiple alignments Some programs give quantitative measures for the significance of the alignment. These are usually based on the chance occurrence of such alignments and depend on the size and composition of the aligned sequences. Empirical measures are also extremely useful for deciding the 'correctness' of the multiple alignment.
Consistency is a powerful measure for correct multiple alignments.
One pitfall to avoid is biassed sequence composition that may lead to trivial alignments. Experimental data can be used in evaluating, and even constructing, multiple alignments. For example, if we know the catalytic site in the aligned proteins we expect the sites to be aligned together and may 'force' that alignment. Such manual alignments can serve as a seed to an alignment with more sequences. Another approach is 'divide and conquer'.