MOTIVATION: Genomic mutations and variations provide insightful information about the functionality of sequence elements and their association with human diseases. Traditionally, variations are identified through analysis of short DNA sequences, usually shorter than 1000 bp per fragment. Optical maps provide both faster and more cost-efficient means for detecting such differences, because a single map can span over 1 million bp. Optical maps are assembled to cover the whole genome, and the accuracy of assembly is critical. RESULTS: We present a computationally efficient model-based method for improving quality of such assemblies. Our method provides very high accuracy even with moderate coverage (<20 x). We utilize a hidden Markov model to represent the consensus map and use the expectation-Maximization algorithm to drive the refinement process. We also provide quality scores to assess the quality of the finished map. AVAILABILITY: Code is available from www.cmb.usc.edu/people/valouev/
MOTIVATION: Genomic mutations and variations provide insightful information about the functionality of sequence elements and their association with human diseases. Traditionally, variations are identified through analysis of short DNA sequences, usually shorter than 1000 bp per fragment. Optical maps provide both faster and more cost-efficient means for detecting such differences, because a single map can span over 1 million bp. Optical maps are assembled to cover the whole genome, and the accuracy of assembly is critical. RESULTS: We present a computationally efficient model-based method for improving quality of such assemblies. Our method provides very high accuracy even with moderate coverage (<20 x). We utilize a hidden Markov model to represent the consensus map and use the expectation-Maximization algorithm to drive the refinement process. We also provide quality scores to assess the quality of the finished map. AVAILABILITY: Code is available from www.cmb.usc.edu/people/valouev/
Authors: Brian Teague; Michael S Waterman; Steven Goldstein; Konstantinos Potamousis; Shiguo Zhou; Susan Reslewic; Deepayan Sarkar; Anton Valouev; Christopher Churas; Jeffrey M Kidd; Scott Kohn; Rodney Runnheim; Casey Lamers; Dan Forrest; Michael A Newton; Evan E Eichler; Marijo Kent-First; Urvashi Surti; Miron Livny; David C Schwartz Journal: Proc Natl Acad Sci U S A Date: 2010-06-01 Impact factor: 11.205
Authors: Kristy L Kounovsky-Shafer; Juan P Hernández-Ortiz; Kyubong Jo; Theo Odijk; Juan J de Pablo; David C Schwartz Journal: Macromolecules Date: 2013-10-22 Impact factor: 5.985
Authors: Jan A L Van Kan; Joost H M Stassen; Andreas Mosbach; Theo A J Van Der Lee; Luigi Faino; Andrew D Farmer; Dimitrios G Papasotiriou; Shiguo Zhou; Michael F Seidl; Eleanor Cottam; Dominique Edel; Matthias Hahn; David C Schwartz; Robert A Dietrich; Stephanie Widdison; Gabriel Scalliet Journal: Mol Plant Pathol Date: 2016-06-09 Impact factor: 5.663
Authors: Aditya Gupta; Michael Place; Steven Goldstein; Deepayan Sarkar; Shiguo Zhou; Konstantinos Potamousis; Jaehyup Kim; Claire Flanagan; Yang Li; Michael A Newton; Natalie S Callander; Peiman Hematti; Emery H Bresnick; Jian Ma; Fotis Asimakopoulos; David C Schwartz Journal: Proc Natl Acad Sci U S A Date: 2015-06-08 Impact factor: 11.205
Authors: Shiguo Zhou; Fusheng Wei; John Nguyen; Mike Bechner; Konstantinos Potamousis; Steve Goldstein; Louise Pape; Michael R Mehan; Chris Churas; Shiran Pasternak; Dan K Forrest; Roger Wise; Doreen Ware; Rod A Wing; Michael S Waterman; Miron Livny; David C Schwartz Journal: PLoS Genet Date: 2009-11-20 Impact factor: 5.917
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