The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Representational Oligonucleotide Microarray Analysis: A High-Resolution Method to Detect Genome Copy Number Variation
Open accessAbstract
We have developed a methodology we call ROMA (representational oligonucleotide microarray analysis), for the detection of the genomic aberrations in cancer and normal humans. By arraying oligonucleotide probes designed from the human genome sequence, and hybridizing with “representations” from cancer and normal cells, we detect regions of the genome with altered “copy number.” We achieve an average resolution of 30 kb throughout the genome, and resolutions as high as a probe every 15 kb are practical. We illustrate the characteristics of probes on the array and accuracy of measurements obtained using ROMA. Using this methodology, we identify variation between cancer and normal genomes, as well as between normal human genomes. In cancer genomes, we readily detect amplifications and large and small homozygous and hemizygous deletions. Between normal human genomes, we frequently detect large (100 kb to 1 Mb) deletions or duplications. Many of these changes encompass known genes. ROMA will assist in the discovery of genes and markers important in cancer, and the discovery of loci that may be important in inherited predispositions to disease.
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Sebat, J., Lakshmi, B., Malhotra, D., Troge, J., Lese-Martin, C., Walsh, T., Yamrom, B., Yoon, S., Krasnitz, A., Kendall, J., et al. (2007) · Science · doi:10.1126/science.1138659 · Cited by 2,795
Self-citationLarge-scale copy number polymorphism in the human genome
Sebat, J., Lakshmi, B., Troge, J., Alexander, J., Young, J., Lundin, P., Månér, S., Massa, H., Walker, M., Chi, M., et al. (2004) · Science · doi:10.1126/science.1098918 · Cited by 2,557
Self-citationMolecular characterization of the tumor microenvironment in breast cancer
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Identification and validation of oncogenes in liver cancer using an integrative oncogenomic approach
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Self-citationA faster circular binary segmentation algorithm for the analysis of array CGH data
Venkatraman, E. S., & Olshen, A. B. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btl646 · Cited by 961
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Metadata
- Authors
- Lucito, R., Healy, J., Alexander, J., Reiner, A., Esposito, D., Chi, M., Rodgers, L., Brady, A., Sebat, J., Troge, J., West, J. A., Rostan, S., Nguyen, K. C. Q., Powers, S., Ye, K. Q., Olshen, A., Venkatraman, E., Norton, L., & Wigler, M.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2003-01-01
- Volume
- 13
- Issue
- 10
- Pages
- 2291-2305
- ISSN
- 1088-9051 (ISSN-L)
- OpenAlex
- W2101833157
- Cited by
- 441
- References
- 26
- Type
- posted content
- Language
- en
- Open access
- bronze
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- Lucito, R., Healy, J., Alexander, J., Reiner, A., Esposito, D., Chi, M., Rodgers, L., Brady, A., Sebat, J., Troge, J., West, J. A., Rostan, S., Nguyen, K. C. Q., Powers, S., Ye, K. Q., Olshen, A., Venkatraman, E., Norton, L., & Wigler, M. (2003). Representational Oligonucleotide Microarray Analysis: A High-Resolution Method to Detect Genome Copy Number Variation. Genome Research. https://doi.org/10.1101/gr.1349003
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