A Visualization Quality Evaluation Method for Multiple Sequence Alignments

Multiple sequence alignments (MSA) method is basic way for the analysis of biology sequences. As dozens of MSA algorithms appears, reasonable and effective quality evaluation method is necessary. Gap-insertion is common phenomenon after MSA, and should be an important factor to evaluate whether MSA is successful. A new MSA score evaluation method was introduced in this paper, which was based on the combination of both row distance of letters and column consensus of sequences. It can be used to evaluate the quality of MSA in the global and local justly and effectively. At same time, two formulas for assessing the distance of different MSA algorithms were derived.