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Field guide to next‐generation DNA sequencers
Abstract
The diversity of available 2 nd and 3 rd generation DNA sequencing platforms is increasing rapidly. Costs for these systems range from <$100 000 to more than $1 000 000, with instrument run times ranging from minutes to weeks. Extensive trade‐offs exist among these platforms. I summarize the major characteristics of each commercially available platform to enable direct comparisons. In terms of cost per megabase (Mb) of sequence, the Illumina and SOLiD platforms are clearly superior (≤$0.10/Mb vs. >$10/Mb for 454 and some Ion Torrent chips). In terms of cost per nonmultiplexed sample and instrument run time, the Pacific Biosciences and Ion Torrent platforms excel, with the 454 GS Junior and Illumina MiSeq also notable in this regard. All platforms allow multiplexing of samples, but details of library preparation, experimental design and data analysis can constrain the options. The wide range of characteristics among available platforms provides opportunities both to conduct groundbreaking studies and to waste money on scales that were previously infeasible. Thus, careful thought about the desired characteristics of these systems is warranted before purchasing or using any of them. Updated information from this guide will be maintained at: http://dna.uga.edu/ and http://tomato.biol.trinity.edu/blog/ .
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“This technology has a relatively low sequencing error rate (<0.1%) (44), and errors are mainly due to substitution errors.”
From Tandem repeats lead to sequence assembly errors and impose multi-level challenges for genome and protein databases (2019) · cites this paper as [44]
Citations
Cites
The sequence and de novo assembly of the giant panda genome
Li, R., Fan, W., Tian, G., Zhu, H., He, L., Cai, J., Huang, Q., Cai, Q., Li, B., Bai, Y., et al. (2010) · Nature · doi:10.1038/nature08696 · Cited by 1,180
Dalloul, R. A., Long, J. A., Zimin, A. V., Aslam, L., Beal, K., Ann Blomberg, L., Bouffard, P., Burt, D. W., Crasta, O., Crooijmans, R. P. M. A., et al. (2010) · PLoS Biology · doi:10.1371/journal.pbio.1000475 · Cited by 416
Research works printed but not linked: 17
- 10.1016/j.nbt.2008.12.009 · DOI · Paper page
- 10.1371/journal.pone.0000197 · DOI
- 10.1111/j.1438-8677.2010.00373.x · DOI
- 10.1038/nmeth.1251 · DOI
- 10.1038/nmeth.1376 · DOI
- 10.1073/pnas.1017351108 · DOI
- 10.1093/nar/gkm435 · DOI
- 10.1093/bib/bbp046 · DOI
- 10.1126/science.1197891 · DOI
- 10.1146/annurev.genom.9.081307.164359 · DOI
- 10.1093/nar/gkm566 · DOI
- 10.1093/bib/bbq020 · DOI · Paper page
- 10.1126/science.331.6018.666 · DOI
- 10.3390/genes1030385 · DOI
- 10.1038/nbt1486 · DOI · Paper page
- 10.1111/j.1365-294X.2009.04489.x · DOI
- 10.1038/463303a · DOI
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Metadata
- Authors
- GLENN, T. C.
- Venue
- Molecular Ecology Resources
- Publisher
- Wiley
- Published
- 2011-05-19
- Volume
- 11
- Issue
- 5
- Pages
- 759-769
- ISSN
- 1755-098X
- 1755-0998
- Cited by
- 940
- References
- 2
- Language
- en
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