title: Automated de novo identification of repeat sequence families in sequenced genomes.
abstract: Repetitive sequences make up a major part of eukaryotic genomes. We have developed an approach for the de novo identification and classification of repeat sequence families that is based on extensions to the usual approach of single linkage clustering of local pairwise alignments between genomic sequences. Our extensions use multiple alignment information to define the boundaries of individual copies of the repeats and to distinguish homologous but distinct repeat element families. When tested on the human genome, our approach was able to properly identify and group known transposable elements. The program, should be useful for first-pass automatic classification of repeats in newly sequenced genomes.
authors.affiliation: Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
authors.forename: Zhirong
authors.initials: Z
authors.lastname: Bao
authors.forename: Sean R
authors.initials: SR
authors.lastname: Eddy
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods / Q000706:statistics & numerical data; D008040:Genetic Linkage / Q000235:genetics; D015894:Genome, Human; D006801:Humans; D005810:Multigene Family / Q000235:genetics*; D012091:Repetitive Sequences, Nucleic Acid / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods / Q000706:statistics & numerical data