Motif recognition and alignment for many sequences by comparison of dot-matrices

Abstract

Calculation of dot-matrices is a widespread tool in the search for sequence similarities. When sequences are distant, even this approach may fail to point out common regions. If several plots calculated for all members of a sequence set consistently displayed a similarity between them, this would increase its credibility. We present an algorithm to delineate dot-plot agreement. A novel procedure based on matrix multiplication is developed to identify common patterns and reliably aligned regions in a set of distantly related sequences. The algorithm finds motifs independent of input sequence lengths and reduces the dependence on gap penalties. When sequences share greater similarity, the same approach converts to a multiple sequence alignment procedure.