Multiple sequence alignment (MSA) is the basis for a wide range of comparative 
sequence analyses from molecular phylogenetics to 3D structure prediction. 
Sophisticated algorithms have been developed for sequence alignment, but in 
practice, many errors can be expected and extensive portions of the MSA are 
unreliable. Hence, it is imperative to understand and characterize the various 
sources of errors in MSAs and to quantify site-specific alignment confidence. In 
this paper, we show that uncertainties in the guide tree used by progressive 
alignment methods are a major source of alignment uncertainty. We use this 
insight to develop a novel method for quantifying the robustness of each 
alignment column to guide tree uncertainty. We build on the widely used 
bootstrap method for perturbing the phylogenetic tree. Specifically, we generate 
a collection of trees and use each as a guide tree in the alignment algorithm, 
thus producing a set of MSAs. We next test the consistency of every column of 
the MSA obtained from the unperturbed guide tree with respect to the set of 
MSAs. We name this measure the "GUIDe tree based AligNment ConfidencE" 
(GUIDANCE) score. Using the Benchmark Alignment data BASE benchmark as well as 
simulation studies, we show that GUIDANCE scores accurately identify errors in 
MSAs. Additionally, we compare our results with the previously published 
Heads-or-Tails score and show that the GUIDANCE score is a better predictor of 
unreliably aligned regions.