The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
High-Throughput Variation Detection and Genotyping Using Microarrays
Open accessAbstract
The genetic dissection of complex traits may ultimately require a large number of SNPs to be genotyped in multiple individuals who exhibit phenotypic variation in a trait of interest. Microarray technology can enable rapid genotyping of variation specific to study samples. To facilitate their use, we have developed an automated statistical method (ABACUS) to analyze microarray hybridization data and applied this method to Affymetrix Variation Detection Arrays (VDAs). ABACUS provides a quality score to individual genotypes, allowing investigators to focus their attention on sites that give accurate information. We have applied ABACUS to an experiment encompassing 32 autosomal and eight X-linked genomic regions, each consisting of ∼50 kb of unique sequence spanning a 100-kb region, in 40 humans. At sufficiently high-quality scores, we are able to read ∼80% of all sites. To assess the accuracy of SNP detection, 108 of 108 SNPs have been experimentally confirmed; an additional 371 SNPs have been confirmed electronically. To access the accuracy of diploid genotypes at segregating autosomal sites, we confirmed 1515 of 1515 homozygous calls, and 420 of 423 (99.29%) heterozygotes. In replicate experiments, consisting of independent amplification of identical samples followed by hybridization to distinct microarrays of the same design, genotyping is highly repeatable. In an autosomal replicate experiment, 813,295 of 813,295 genotypes are called identically (including 351 heterozygotes); at an X-linked locus in males (haploid), 841,236 of 841,236 sites are called identically.
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Cites
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
Altschul, S. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.17.3389 · Cited by 73,302
Initial sequencing and analysis of the human genome
International Human Genome Sequencing Consortium, Whitehead Institute for Biomedical Research, C. F. G. R., Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C., Zody, M. C., Baldwin, J., Devon, K., Dewar, K., et al. (2001) · Nature · doi:10.1038/35057062 · Cited by 24,216
Self-citationThe sequence of the human genome
Venter, J. C., Adams, M. D., Myers, E. W., Li, P. W., Mural, R. J., Sutton, G. G., Smith, H. O., Yandell, M., Evans, C. A., Holt, R. A., et al. (2001) · Science · doi:10.1126/science.1058040 · Cited by 13,909
Identification of common molecular subsequences
Smith, T. F., & Waterman, M. S. (1981) · Journal of Molecular Biology · doi:10.1016/0022-2836(81)90087-5 · Cited by 9,940
Base-Calling of Automated Sequencer Traces Using Phred. I. Accuracy Assessment
Ewing, B., Hillier, L., Wendl, M. C., & Green, P. (1998) · Genome Research · doi:10.1101/gr.8.3.175 · Cited by 6,967
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
On the number of segregating sites in genetical models without recombination
Watterson, G. A. (1975) · Theoretical Population Biology · doi:10.1016/0040-5809(75)90020-9 · Cited by 3,915
Genetic Dissection of Complex Traits
Lander, E. S., & Schork, N. J. (1994) · Science · doi:10.1126/science.8091226 · Cited by 3,413
Consed: A Graphical Tool for Sequence Finishing
Gordon, D., Abajian, C., & Green, P. (1998) · Genome Research · doi:10.1101/gr.8.3.195 · Cited by 3,302
A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms
The International SNP Map Working Group, Laboratories:, C. S. H., Sachidanandam, R., Weissman, D., Schmidt, S. C., Kakol, J. M., Stein, L. D., National Center for Biotechnology Information:, Marth, G., Sherry, S., et al. (2001) · Nature · doi:10.1038/35057149 · Cited by 2,977
Cited by
LaFramboise, T. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp552 · Cited by 467
“With the advent of the 100K array, the manufacturer switched to a dynamic model algorithm (24).”
MethodA common sex-dependent mutation in a RET enhancer underlies Hirschsprung disease risk
Emison, E. S., McCallion, A. S., Kashuk, C. S., Bush, R. T., Grice, E., Lin, S., Portnoy, M. E., Cutler, D. J., Green, E. D., & Chakravarti, A. (2005) · Nature · doi:10.1038/nature03467 · Cited by 462
Self-citationEfficient discovery of DNA polymorphisms in natural populations by Ecotilling
Comai, L., Young, K., Till, B. J., Reynolds, S. H., Greene, E. A., Codomo, C. A., Enns, L. C., Johnson, J. E., Burtner, C., Odden, A. R., et al. (2004) · The Plant Journal · doi:10.1111/j.0960-7412.2003.01999.x · Cited by 451
Matsuzaki, H., Loi, H., Dong, S., Tsai, Y.-Y., Fang, J., Law, J., Di, X., Liu, W.-M., Yang, G., Liu, G., et al. (2004) · Genome Research · doi:10.1101/gr.2014904 · Cited by 320
Graze, R. M., McIntyre, L. M., Main, B. J., Wayne, M. L., & Nuzhdin, S. V. (2009) · Genetics · doi:10.1534/genetics.109.105957 · Cited by 100
Metadata
- Authors
- Cutler, D. J., Zwick, M. E., Carrasquillo, M. M., Yohn, C. T., Tobin, K. P., Kashuk, C., Mathews, D. J., Shah, N. A., Eichler, E. E., Warrington, J. A., & Chakravarti, A.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2001-10-15
- Volume
- 11
- Issue
- 11
- Pages
- 1913-1925
- ISSN
- 1088-9051 (ISSN-L)
- 1549-5469
- OpenAlex
- W1958158305
- Cited by
- 277
- References
- 36
- Type
- posted content
- Language
- en
- Open access
- green
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