Giuseppe Narzisi1, Bud Mishra. 1. Courant Institute of Mathematical Sciences, New York University, New York, NY 10012, USA. narzisi@nyu.edu
Abstract
MOTIVATION: Mired by its connection to a well-known -complete combinatorial optimization problem-namely, the Shortest Common Superstring Problem (SCSP)-historically, the whole-genome sequence assembly (WGSA) problem has been assumed to be amenable only to greedy and heuristic methods. By placing efficiency as their first priority, these methods opted to rely only on local searches, and are thus inherently approximate, ambiguous or error prone, especially, for genomes with complex structures. Furthermore, since choice of the best heuristics depended critically on the properties of (e.g. errors in) the input data and the available long range information, these approaches hindered designing an error free WGSA pipeline. RESULTS: We dispense with the idea of limiting the solutions to just the approximated ones, and instead favor an approach that could potentially lead to an exhaustive (exponential-time) search of all possible layouts. Its computational complexity thus must be tamed through a constrained search (Branch-and-Bound) and quick identification and pruning of implausible overlays. For his purpose, such a method necessarily relies on a set of score functions (oracles) that can combine different structural properties (e.g. transitivity, coverage, physical maps, etc.). We give a detailed description of this novel assembly framework, referred to as Scoring-and-Unfolding Trimmed Tree Assembler (SUTTA), and present experimental results on several bacterial genomes using next-generation sequencing technology data. We also report experimental evidence that the assembly quality strongly depends on the choice of the minimum overlap parameter k. AVAILABILITY AND IMPLEMENTATION: SUTTA's binaries are freely available to non-profit institutions for research and educational purposes at http://www.bioinformatics.nyu.edu.
MOTIVATION: Mired by its connection to a well-known -complete combinatorial optimization problem-namely, the Shortest Common Superstring Problem (SCSP)-historically, the whole-genome sequence assembly (WGSA) problem has been assumed to be amenable only to greedy and heuristic methods. By placing efficiency as their first priority, these methods opted to rely only on local searches, and are thus inherently approximate, ambiguous or error prone, especially, for genomes with complex structures. Furthermore, since choice of the best heuristics depended critically on the properties of (e.g. errors in) the input data and the available long range information, these approaches hindered designing an error free WGSA pipeline. RESULTS: We dispense with the idea of limiting the solutions to just the approximated ones, and instead favor an approach that could potentially lead to an exhaustive (exponential-time) search of all possible layouts. Its computational complexity thus must be tamed through a constrained search (Branch-and-Bound) and quick identification and pruning of implausible overlays. For his purpose, such a method necessarily relies on a set of score functions (oracles) that can combine different structural properties (e.g. transitivity, coverage, physical maps, etc.). We give a detailed description of this novel assembly framework, referred to as Scoring-and-Unfolding Trimmed Tree Assembler (SUTTA), and present experimental results on several bacterial genomes using next-generation sequencing technology data. We also report experimental evidence that the assembly quality strongly depends on the choice of the minimum overlap parameter k. AVAILABILITY AND IMPLEMENTATION: SUTTA's binaries are freely available to non-profit institutions for research and educational purposes at http://www.bioinformatics.nyu.edu.
Authors: Michael C Schatz; Adam M Phillippy; Daniel D Sommer; Arthur L Delcher; Daniela Puiu; Giuseppe Narzisi; Steven L Salzberg; Mihai Pop Journal: Brief Bioinform Date: 2011-12-23 Impact factor: 11.622
Authors: Soohong Kim; Anna Gottfried; Ron R Lin; Thomas Dertinger; Andrew S Kim; Sangyoon Chung; Ryan A Colyer; Elmar Weinhold; Shimon Weiss; Yuval Ebenstein Journal: Angew Chem Int Ed Engl Date: 2012-02-16 Impact factor: 15.336
Authors: Michal Levy-Sakin; Assaf Grunwald; Soohong Kim; Natalie R Gassman; Anna Gottfried; Josh Antelman; Younggyu Kim; Sam O Ho; Robin Samuel; Xavier Michalet; Ron R Lin; Thomas Dertinger; Andrew S Kim; Sangyoon Chung; Ryan A Colyer; Elmar Weinhold; Shimon Weiss; Yuval Ebenstein Journal: ACS Nano Date: 2013-12-20 Impact factor: 15.881
Authors: Giuseppe Narzisi; Jason A O'Rawe; Ivan Iossifov; Han Fang; Yoon-Ha Lee; Zihua Wang; Yiyang Wu; Gholson J Lyon; Michael Wigler; Michael C Schatz Journal: Nat Methods Date: 2014-08-17 Impact factor: 28.547
Authors: Henry C Lin; Steve Goldstein; Lee Mendelowitz; Shiguo Zhou; Joshua Wetzel; David C Schwartz; Mihai Pop Journal: BMC Bioinformatics Date: 2012-08-02 Impact factor: 3.169