title: Decomposition of overlapping patterns by cumulative local cross-correlation.
abstract: A large portion of the usual eukaryotic genome is comprised of repetitive sequences. A common situation, when several related but different repeat families share the same conserved motif, complicates repeat classification and repeat boundary definition. If the repeats are aligned by the motif position, then the sequence profile (pattern) resulting from the alignment will represent overlapping of the profiles (patterns) corresponding to the individual families. A novel algorithm for the decomposition of overlapping patterns is proposed. It can be used with both continuous and gapped patterns. The technique is based on accumulation of simultaneously occurring pattern features found by cross-correlation procedure with limited lag length; thus, the name is Cumulative Local Cross-Correlation (referred further as CLCC). Its sensitivity is tested on human genomic sequences. Software implementation of the algorithm is available on request from the author.
authors.affiliation: Genome Diversity Center, Institute of Evolution, University of Haifa, Mount Carmel, Haifa 31905, Israel. skogan@research.haifa.ac.il
authors.forename: Simon B
authors.initials: SB
authors.lastname: Kogan
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D015894:Genome, Human / Q000235:genetics; D006801:Humans; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated / Q000379:methods*; D012091:Repetitive Sequences, Nucleic Acid / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D013223:Statistics as Topic