| Title |
Assemblathon 1: A competitive assessment of de novo short read assembly methods
|
|---|---|
| Published in |
Genome Research, September 2011
|
| DOI | 10.1101/gr.126599.111 |
| Pubmed ID | |
| Authors |
Dent Earl, Keith Bradnam, John St. John, Aaron Darling, Dawei Lin, Joseph Fass, Hung On Ken Yu, Vince Buffalo, Daniel R. Zerbino, Mark Diekhans, Ngan Nguyen, Pramila Nuwantha Ariyaratne, Wing-Kin Sung, Zemin Ning, Matthias Haimel, Jared T. Simpson, Nuno A. Fonseca, İnanç Birol, T. Roderick Docking, Isaac Y. Ho, Daniel S. Rokhsar, Rayan Chikhi, Dominique Lavenier, Guillaume Chapuis, Delphine Naquin, Nicolas Maillet, Michael C. Schatz, David R. Kelley, Adam M. Phillippy, Sergey Koren, Shiaw-Pyng Yang, Wei Wu, Wen-Chi Chou, Anuj Srivastava, Timothy I. Shaw, J. Graham Ruby, Peter Skewes-Cox, Miguel Betegon, Michelle T. Dimon, Victor Solovyev, Igor Seledtsov, Petr Kosarev, Denis Vorobyev, Ricardo Ramirez-Gonzalez, Richard Leggett, Dan MacLean, Fangfang Xia, Ruibang Luo, Zhenyu Li, Yinlong Xie, Binghang Liu, Sante Gnerre, Iain MacCallum, Dariusz Przybylski, Filipe J. Ribeiro, Shuangye Yin, Ted Sharpe, Giles Hall, Paul J. Kersey, Richard Durbin, Shaun D. Jackman, Jarrod A. Chapman, Xiaoqiu Huang, Joseph L. DeRisi, Mario Caccamo, Yingrui Li, David B. Jaffe, Richard E. Green, David Haussler, Ian Korf, Benedict Paten |
| Abstract |
Low-cost short read sequencing technology has revolutionized genomics, though it is only just becoming practical for the high-quality de novo assembly of a novel large genome. We describe the Assemblathon 1 competition, which aimed to comprehensively assess the state of the art in de novo assembly methods when applied to current sequencing technologies. In a collaborative effort, teams were asked to assemble a simulated Illumina HiSeq data set of an unknown, simulated diploid genome. A total of 41 assemblies from 17 different groups were received. Novel haplotype aware assessments of coverage, contiguity, structure, base calling, and copy number were made. We establish that within this benchmark: (1) It is possible to assemble the genome to a high level of coverage and accuracy, and that (2) large differences exist between the assemblies, suggesting room for further improvements in current methods. The simulated benchmark, including the correct answer, the assemblies, and the code that was used to evaluate the assemblies is now public and freely available from http://www.assemblathon.org/. |
X Demographics
The data shown below were collected from the profiles of 48 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 15% |
| United Kingdom | 6 | 13% |
| Australia | 2 | 4% |
| Hong Kong | 1 | 2% |
| France | 1 | 2% |
| Japan | 1 | 2% |
| Spain | 1 | 2% |
| Sao Tome and Principe | 1 | 2% |
| Germany | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 25 | 52% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 34 | 71% |
| Scientists | 18 | 38% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 1,114 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 45 | 4% |
| Germany | 17 | 2% |
| United Kingdom | 15 | 1% |
| France | 8 | <1% |
| Brazil | 8 | <1% |
| Spain | 7 | <1% |
| Canada | 7 | <1% |
| Sweden | 6 | <1% |
| Denmark | 5 | <1% |
| Other | 53 | 5% |
| Unknown | 943 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 288 | 26% |
| Student > Ph. D. Student | 266 | 24% |
| Student > Master | 158 | 14% |
| Student > Bachelor | 78 | 7% |
| Other | 60 | 5% |
| Other | 197 | 18% |
| Unknown | 67 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 651 | 58% |
| Biochemistry, Genetics and Molecular Biology | 170 | 15% |
| Computer Science | 108 | 10% |
| Medicine and Dentistry | 17 | 2% |
| Environmental Science | 16 | 1% |
| Other | 64 | 6% |
| Unknown | 88 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 98. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 February 2024.
All research outputs
#440,405
of 25,837,817 outputs
Outputs from Genome Research
#100
of 4,469 outputs
Outputs of similar age
#1,501
of 133,756 outputs
Outputs of similar age from Genome Research
#3
of 58 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,469 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.9. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 133,756 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.