Pattern overlapping decomposition by Cumulative Local Cross-Correlation

Abstract

Background Nucleotide sequences contain multiple codes responsible for organism's functioning and structure. They can be investigated by various signal processing methods. These techniques are well suited for indication of frequently encountered sequence motifs (i.e., repeats). However, if there are two or more codes containing the same motif, the local nucleotide distribution (i.e., profile), resulting from sequence alignment by the motif position, will represent overlapping of the code patterns. Results The novel algorithm for decomposition of pattern overlapping is proposed. It is capable to work with dispersed repeats as well. The algorithm is based on cross-correlation procedure applied locally in a cumulative fashion. Its sensitivity was tested on human genomic sequences. Conclusions Cumulative Local Cross-Correlation was successfully used to decompose overlapping of nucleotide patterns in human genomic sequences. Being very general technique (as general as cross-correlation), it can be easily adopted in other signal processing applications and naturally extended for multidimensional cases. Software implementation of the algorithm is available on request from the authors.