title: Finding anchors for genomic sequence comparison.
abstract: Recent sequencing of the human and other mammalian genomes has brought about the necessity to align them, to identify and characterize their commonalities and differences. Programs that align whole genomes generally use a seed-and-extend technique, starting from exact or near-exact matches and selecting a reliable subset of these, called anchors, and then filling in the remaining portions between the anchors using a combination of local and global alignment algorithms, but their choices for the parameters so far have been primarily heuristic. We present a statistical framework and practical methods for selecting a set of matches that is both sensitive and specific and can constitute a reliable set of anchors for a one-to-one mapping of two genomes from which a whole-genome alignment can be built. Starting from exact matches, we introduce a novel per-base repeat annotation, the Z-score, from which noise and repeat filtering conditions are explored. Dynamic programming-based chaining algorithms are also evaluated as context-based filters. We apply the methods described here to the comparison of two progressive assemblies of the human genome, NCBI build 28 and build 34 (www.genome.ucsc.edu), and show that a significant portion of the two genomes can be found in selected exact matches, with very limited amount of sequence duplication.
authors.affiliation: Informatics Research, Celera/Applied Biosystems, 45 West Gude Drive, Rockville, MD 20850, USA.
authors.forename: Ross A
authors.initials: RA
authors.lastname: Lippert
authors.forename: Xiaoyue
authors.initials: X
authors.lastname: Zhao
authors.forename: Liliana
authors.initials: L
authors.lastname: Florea
authors.forename: Clark
authors.initials: C
authors.lastname: Mobarry
authors.forename: Sorin
authors.initials: S
authors.lastname: Istrail
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs; D002874:Chromosome Mapping; D016678:Genome; D008957:Models, Genetic; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software