Abstract
In this paper, we propose a method for multiple sequence alignment, LemK_MSA, which integrates Lempel-Ziv based sequence vectorization and k-means clustering analysis. LemK_MSA converts multiple sequence alignment into corresponding 10-dimensional vector alignment by 10 types of copy modes. Then it uses k-means algorithm and NJ algorithm to divide the sequences into several groups and calculate guide tree of each part with the vectors of the sequences. A complete guide tree for multiple sequence alignment could be constructed by merging guide tree of every group. Thus, the time efficiency of processing multiple sequence alignment, especially for large-scale sequences, can be improved. The high-throughput mouse antibody sequences are used to validate the proposed method. Compared to ClustalW, MAFFT and Mbed, LemK_MSA is more than ten times efficient while ensuring the alignment accuracy at the same time. LemK_MSA also provides an effective method to analyze the evolutionary relationship and structural features among high-throughput sequences.
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