Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species.
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 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.
Bradnam, KR; Fass, JN; Alexandrov, A; Baranay, P; Bechner, M; Birol, I; Boisvert, S; Chapman, JA; Chapuis, G; Chikhi, R; Chitsaz, H; Chou, W-C; Corbeil, J; Del Fabbro, C; Docking, TR; Durbin, R; Earl, D; Emrich, S; Fedotov, P; Fonseca, NA; Ganapathy, G; Gibbs, RA; Gnerre, S; Godzaridis, E; Goldstein, S; Haimel, M; Hall, G; Haussler, D; Hiatt, JB; Ho, IY; Howard, J; Hunt, M; Jackman, SD; Jaffe, DB; Jarvis, ED; Jiang, H; Kazakov, S; Kersey, PJ; Kitzman, JO; Knight, JR; Koren, S; Lam, T-W; Lavenier, D; Laviolette, F; Li, Y; Li, Z; Liu, B; Liu, Y; Luo, R; Maccallum, I; Macmanes, MD; Maillet, N; Melnikov, S; Naquin, D; Ning, Z; Otto, TD; Paten, B; Paulo, OS; Phillippy, AM; Pina-Martins, F; Place, M; Przybylski, D; Qin, X; Qu, C; Ribeiro, FJ; Richards, S; Rokhsar, DS; Ruby, JG; Scalabrin, S; Schatz, MC; Schwartz, DC; Sergushichev, A; Sharpe, T; Shaw, TI; Shendure, J; Shi, Y; Simpson, JT; Song, H; Tsarev, F; Vezzi, F; Vicedomini, R; Vieira, BM; Wang, J; Worley, KC; Yin, S; Yiu, S-M; Yuan, J; Zhang, G; Zhang, H; Zhou, S; Korf, IF
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