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arxiv: 1301.5406 · v3 · submitted 2013-01-23 · 🧬 q-bio.GN

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Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species

Keith R. Bradnam (1) , Joseph N. Fass (1) , Anton Alexandrov (36) , Paul Baranay (2) , Michael Bechner (39) , \.Inan\c{c} Birol (33) , S\'ebastien Boisvert , (11)
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Jarrod A. Chapman (20) Guillaume Chapuis (7 9) Rayan Chikhi (7 Hamidreza Chitsaz (6) Wen-Chi Chou (14 16) Jacques Corbeil (10 13) Cristian Del Fabbro (17) T. Roderick Docking (33) Richard Durbin (34) Dent Earl (40) Scott Emrich (3) Pavel Fedotov (36) Nuno A. Fonseca (30 35) Ganeshkumar Ganapathy (38) Richard A. Gibbs (32) Sante Gnerre (22) \'El\'enie Godzaridis (11) Steve Goldstein (39) Matthias Haimel (30) Giles Hall (22) David Haussler (40) Joseph B. Hiatt (41) Isaac Y. Ho (20) Jason Howard (38) Martin Hunt (34) Shaun D. Jackman (33) David B Jaffe (22) Erich Jarvis (38) Huaiyang Jiang (32) Sergey Kazakov (36) Paul J. Kersey (30) Jacob O. Kitzman (41) James R. Knight (37) Sergey Koren (24 25) Tak-Wah Lam (29) Dominique Lavenier (7 8 Fran\c{c}ois Laviolette (12) Yingrui Li (28 29) Zhenyu Li (28) Binghang Liu (28) Yue Liu (32) Ruibang Luo (28 Iain MacCallum (22) Matthew D MacManes (5) Nicolas Maillet (8 Sergey Melnikov (36) Bruno Miguel Vieira (31) Delphine Naquin (8 Zemin Ning (34) Thomas D. Otto (34) Benedict Paten (40) Oct\'avio S. Paulo (31) Adam M. Phillippy (24 Francisco Pina-Martins (31) Michael Place (39) Dariusz Przybylski (22) Xiang Qin (32) Carson Qu (32) Filipe J Ribeiro (22) Stephen Richards (32) Daniel S. Rokhsar (20 21) J. Graham Ruby (26 27) Simone Scalabrin (17) Michael C. Schatz (4) David C. Schwartz (39) Alexey Sergushichev (36) Ted Sharpe (22) Timothy I. Shaw (14 15) Jay Shendure (41) Yujian Shi (28) Jared T. Simpson (34) Henry Song (32) Fedor Tsarev (36) Francesco Vezzi (19) Riccardo Vicedomini (17 18) Jun Wang (28) Kim C. Worley (32) Shuangye Yin (22) Siu-Ming Yiu (29) Jianying Yuan (28) Guojie Zhang (28) Hao Zhang (28) Shiguo Zhou (39) Ian F. Korf (1) ((1) UC Davis (2) Yale University (3) University of Notre Dame (4) Cold Spring Harbor Laboratory (5) UC Berkeley (6) Wayne State University (7) ENS Cachan/IRISA (8) INRIA (9) CNRS/Symbiose IRISA (10) CHUQ Research Center (11) Laval University (12) Laval University (13) Laval University (14) University of Georgia (15) University of Georgia (16) Institute of Aging Research (17) University of Udine (18) University of Udine (19) KTH Royal Institute of Technology (20) DOE Joint Genome Institute (21) UC Berkeley (22) Broad Institute (23) New York Genome Center (24) National Biodefense Analysis Countermeasures Center (25) University of Maryland (26) UC San Francisco (27) Howard Hughes Medical Institute (28) BGI-Shenzhen (29) HKU-BGI Bioinformatics Algorithms Core Technology Research Laboratory (30) EMBL-European Bioinformatics Institute (31) University of Lisbon (32) Baylor College of Medicine (33) British Columbia Cancer Agency (34) The Wellcome Trust Sanger Institute (35) CRACS - INESC TEC (36) National Research University of Information Technology (37) 454 Life Sciences (38) Duke University Medical Center (39) UW-Biotechnology Center (40) UC Santa Cruz (41) University of Washington)
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keywords genomeassemblyassembliesdatasequencesassemblathonassembledassess
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Background - The process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly. Results - In Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies. Conclusions - Many current genome assemblers produced useful assemblies, containing a significant representation of their genes, regulatory sequences, and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another.

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