The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Next-Generation Sequencing: From Basic Research to Diagnostics
Abstract
Background: For the past 30 years, the Sanger method has been the dominant approach and gold standard for DNA sequencing. The commercial launch of the first massively parallel pyrosequencing platform in 2005 ushered in the new era of high-throughput genomic analysis now referred to as next-generation sequencing (NGS). Content: This review describes fundamental principles of commercially available NGS platforms. Although the platforms differ in their engineering configurations and sequencing chemistries, they share a technical paradigm in that sequencing of spatially separated, clonally amplified DNA templates or single DNA molecules is performed in a flow cell in a massively parallel manner. Through iterative cycles of polymerase-mediated nucleotide extensions or, in one approach, through successive oligonucleotide ligations, sequence outputs in the range of hundreds of megabases to gigabases are now obtained routinely. Highlighted in this review are the impact of NGS on basic research, bioinformatics considerations, and translation of this technology into clinical diagnostics. Also presented is a view into future technologies, including real-time single-molecule DNA sequencing and nanopore-based sequencing. Summary: In the relatively short time frame since 2005, NGS has fundamentally altered genomics research and allowed investigators to conduct experiments that were previously not technically feasible or affordable. The various technologies that constitute this new paradigm continue to evolve, and further improvements in technology robustness and process streamlining will pave the path for translation into clinical diagnostics.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
RNA-Seq: a revolutionary tool for transcriptomics
Wang, Z., Gerstein, M., & Snyder, M. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2484 · Cited by 13,174
High-Resolution Profiling of Histone Methylations in the Human Genome
Barski, A., Cuddapah, S., Cui, K., Roh, T.-Y., Schones, D. E., Wang, Z., Wei, G., Chepelev, I., & Zhao, K. (2007) · Cell · doi:10.1016/j.cell.2007.05.009 · Cited by 6,845
Base-Calling of Automated Sequencer Traces Using Phred. II. Error Probabilities
Ewing, B., & Green, P. (1998) · Genome Research · doi:10.1101/gr.8.3.186 · Cited by 5,439
Alternative isoform regulation in human tissue transcriptomes
Wang, E. T., Sandberg, R., Luo, S., Khrebtukova, I., Zhang, L., Mayr, C., Kingsmore, S. F., Schroth, G. P., & Burge, C. B. (2008) · Nature · doi:10.1038/nature07509 · Cited by 5,181
Pan, Q., Shai, O., Lee, L. J., Frey, B. J., & Blencowe, B. J. (2008) · Nature Genetics · doi:10.1038/ng.259 · Cited by 3,951
Accurate whole human genome sequencing using reversible terminator chemistry
Bentley, D. R., Balasubramanian, S., Swerdlow, H. P., Smith, G. P., Milton, J., Brown, C. G., Hall, K. P., Evers, D. J., Barnes, C. L., Bignell, H. R., et al. (2008) · Nature · doi:10.1038/nature07517 · Cited by 3,684
SOAP: Short oligonucleotide alignment program
Li, R., Li, Y., Kristiansen, K., & Wang, J. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn025 · Cited by 3,597
Somatic mutations affect key pathways in lung adenocarcinoma
Ding, L., Getz, G., Wheeler, D. A., Mardis, E. R., McLellan, M. D., Cibulskis, K., Sougnez, C., Greulich, H., Muzny, D. M., Morgan, M. B., et al. (2008) · Nature · doi:10.1038/nature07423 · Cited by 2,681
The complete genome of an individual by massively parallel DNA sequencing
Wheeler, D. A., Srinivasan, M., Egholm, M., Shen, Y., Chen, L., McGuire, A., He, W., Chen, Y.-J., Makhijani, V., Roth, G. T., et al. (2008) · Nature · doi:10.1038/nature06884 · Cited by 1,838
Cited by
Chiu, C. Y., & Miller, S. A. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0113-7 · Cited by 1,620
The sequence of sequencers: The history of sequencing DNA
Heather, J. M., & Chain, B. (2016) · Genomics · doi:10.1016/j.ygeno.2015.11.003 · Cited by 1,397
“…fi rst high-throughput sequencing (HTS) machine widely available to consumers was the original 454 machine, called the GS 20, which was later superceded by the 454 GS FLX, which offered a greater number of reads (by having more wells in the ‘ picotiter ’ plate) as well as better quality data [56].”
BackgroundMethodInfluentialDefining the healthy “core microbiome” of oral microbial communities
Zaura, E., Keijser, B. J., Huse, S. M., & Crielaard, W. (2009) · BMC Microbiology · doi:10.1186/1471-2180-9-259 · Cited by 1,323
The impact of next-generation sequencing on genomics
Zhang, J., Chiodini, R., Badr, A., & Zhang, G. (2011) · Journal of Genetics and Genomics · doi:10.1016/j.jgg.2011.02.003 · Cited by 577
“More detailed technical description of these platforms are available elsewhere (Mardis, 2008a,b, 2009; Schuster, 2008; Shendure and Ji, 2008; Ansorge, 2009; Harismendy et al., 2009; Tucker et al., 2009; Voelkerding et al., 2009; Metzker, 2010; Ng and Kirkness, 2010).”
BackgroundNext generation sequencing and its applications in forensic genetics
Børsting, C., & Morling, N. (2015) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2015.02.002 · Cited by 460
Metadata
- Authors
- Voelkerding, K. V., Dames, S. A., & Durtschi, J. D.
- Venue
- Clinical Chemistry
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-04-01
- Volume
- 55
- Issue
- 4
- Pages
- 641-658
- ISSN
- 0009-9147 (ISSN-L)
- 1530-8561
- OpenAlex
- W2169002484
- Cited by
- 839
- References
- 16
- FWCI
- 25.81
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Next-Generation Sequencing: From Basic Research to Diagnostics. https://app.cochat.ai/papers/10.1373/clinchem.2008.112789
- The paper
- Voelkerding, K. V., Dames, S. A., & Durtschi, J. D. (2009). Next-Generation Sequencing: From Basic Research to Diagnostics. Clinical Chemistry. https://doi.org/10.1373/clinchem.2008.112789
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
