A measure of the similarity of sets of sequences not requiring sequence alignment

Abstract

Determination of first- and second-order Markov chain homogeneity of sets of nuclear eukaryotic DNA sequences, both coding and noncoding, finds similarities imperceptible to the standard Needleman-Wunsch base matching or dot-matrix algorithms. These measures of the similarities of the distributions of adjacent pairs or triplets are in agreement with accepted evolutionary-tree topologies. Hierarchical clustering of the distributions of doublets of 30 miscellaneous coding sequences gives clusters in reasonable agreement with accepted biological classifications. In addition to similarity by homology, there is also observed similarity of disparate genes in the same organism--for example, all three disparate yeast genes (two enzymes and actin) form a well-distinguished cluster.