MOTIVATION: Multiple sequence alignment is a cornerstone of comparative genomics. Much work has been done to improve methods for this task, particularly for the alignment of small sequences, and especially for amino acid sequences. However, less work has been done in making promising methods that work on the small-scale practically for the alignment of much larger genomic sequences. RESULTS: We take the method of probabilistic consistency alignment and make it practical for the alignment of large genomic sequences. In so doing we develop a set of new technical methods, combined in a framework we term 'sequence progressive alignment', because it allows us to iteratively compute an alignment by passing over the input sequences from left to right. The result is that we massively decrease the memory consumption of the program relative to a naive implementation. The general engineering of the challenges faced in scaling such a computationally intensive process offer valuable lessons for planning related large-scale sequence analysis algorithms. We also further show the strong performance of Pecan using an extended analysis of ancient repeat alignments. Pecan is now one of the default alignment programs that has and is being used by a number of whole-genome comparative genomic projects. AVAILABILITY: The Pecan program is freely available at http://www.ebi.ac.uk/ approximately bjp/pecan/ Pecan whole genome alignments can be found in the Ensembl genome browser.
MOTIVATION: Multiple sequence alignment is a cornerstone of comparative genomics. Much work has been done to improve methods for this task, particularly for the alignment of small sequences, and especially for amino acid sequences. However, less work has been done in making promising methods that work on the small-scale practically for the alignment of much larger genomic sequences. RESULTS: We take the method of probabilistic consistency alignment and make it practical for the alignment of large genomic sequences. In so doing we develop a set of new technical methods, combined in a framework we term 'sequence progressive alignment', because it allows us to iteratively compute an alignment by passing over the input sequences from left to right. The result is that we massively decrease the memory consumption of the program relative to a naive implementation. The general engineering of the challenges faced in scaling such a computationally intensive process offer valuable lessons for planning related large-scale sequence analysis algorithms. We also further show the strong performance of Pecan using an extended analysis of ancient repeat alignments. Pecan is now one of the default alignment programs that has and is being used by a number of whole-genome comparative genomic projects. AVAILABILITY: The Pecan program is freely available at http://www.ebi.ac.uk/ approximately bjp/pecan/ Pecan whole genome alignments can be found in the Ensembl genome browser.
Authors: Benedict Paten; Dent Earl; Ngan Nguyen; Mark Diekhans; Daniel Zerbino; David Haussler Journal: Genome Res Date: 2011-06-10 Impact factor: 9.043
Authors: Daniel E Neafsey; Bridget M Barker; Thomas J Sharpton; Jason E Stajich; Daniel J Park; Emily Whiston; Chiung-Yu Hung; Cody McMahan; Jared White; Sean Sykes; David Heiman; Sarah Young; Qiandong Zeng; Amr Abouelleil; Lynne Aftuck; Daniel Bessette; Adam Brown; Michael FitzGerald; Annie Lui; J Pendexter Macdonald; Margaret Priest; Marc J Orbach; John N Galgiani; Theo N Kirkland; Garry T Cole; Bruce W Birren; Matthew R Henn; John W Taylor; Steven D Rounsley Journal: Genome Res Date: 2010-06-01 Impact factor: 9.043
Authors: Kishwar Shafin; Trevor Pesout; Ryan Lorig-Roach; Marina Haukness; Hugh E Olsen; Colleen Bosworth; Joel Armstrong; Kristof Tigyi; Nicholas Maurer; Sergey Koren; Fritz J Sedlazeck; Tobias Marschall; Simon Mayes; Vania Costa; Justin M Zook; Kelvin J Liu; Duncan Kilburn; Melanie Sorensen; Katy M Munson; Mitchell R Vollger; Jean Monlong; Erik Garrison; Evan E Eichler; Sofie Salama; David Haussler; Richard E Green; Mark Akeson; Adam Phillippy; Karen H Miga; Paolo Carnevali; Miten Jain; Benedict Paten Journal: Nat Biotechnol Date: 2020-05-04 Impact factor: 54.908
Authors: Paul Flicek; Bronwen L Aken; Benoit Ballester; Kathryn Beal; Eugene Bragin; Simon Brent; Yuan Chen; Peter Clapham; Guy Coates; Susan Fairley; Stephen Fitzgerald; Julio Fernandez-Banet; Leo Gordon; Stefan Gräf; Syed Haider; Martin Hammond; Kerstin Howe; Andrew Jenkinson; Nathan Johnson; Andreas Kähäri; Damian Keefe; Stephen Keenan; Rhoda Kinsella; Felix Kokocinski; Gautier Koscielny; Eugene Kulesha; Daniel Lawson; Ian Longden; Tim Massingham; William McLaren; Karine Megy; Bert Overduin; Bethan Pritchard; Daniel Rios; Magali Ruffier; Michael Schuster; Guy Slater; Damian Smedley; Giulietta Spudich; Y Amy Tang; Stephen Trevanion; Albert Vilella; Jan Vogel; Simon White; Steven P Wilder; Amonida Zadissa; Ewan Birney; Fiona Cunningham; Ian Dunham; Richard Durbin; Xosé M Fernández-Suarez; Javier Herrero; Tim J P Hubbard; Anne Parker; Glenn Proctor; James Smith; Stephen M J Searle Journal: Nucleic Acids Res Date: 2009-11-11 Impact factor: 16.971