title: Split-alignment of genomes finds orthologies more accurately.
abstract: We present a new pair-wise genome alignment method, based on a simple concept of finding an optimal set of local alignments. It gains accuracy by not masking repeats, and by using a statistical model to quantify the (un)ambiguity of each alignment part. Compared to previous animal genome alignments, it aligns thousands of locations differently and with much higher similarity, strongly suggesting that the previous alignments are non-orthologous. The previous methods suffer from an overly-strong assumption of long un-rearranged blocks. The new alignments should help find interesting and unusual features, such as fast-evolving elements and micro-rearrangements, which are confounded by alignment errors.
authors.affiliation: Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan. martin@cbrc.jp.
authors.forename: Martin C
authors.initials: MC
authors.lastname: Frith
authors.affiliation: Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan. kawaguchi-rs@cb.k.u-tokyo.ac.jp.|Department of Computational Biology, Faculty of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561, Japan. kawaguchi-rs@cb.k.u-tokyo.ac.jp.
authors.forename: Risa
authors.initials: R
authors.lastname: Kawaguchi
mesh_terms: D000465:Algorithms; D000818:Animals; D001483:Base Sequence; D004285:Dogs; D004330:Drosophila / Q000145:classification / Q000235:genetics; D016678:Genome; D006801:Humans; D051379:Mice; D008957:Models, Genetic; D015233:Models, Statistical; D008969:Molecular Sequence Data; D016415:Sequence Alignment; D026801:Synteny