The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data
Open accessAbstract
Genome-wide expression profiling is a powerful tool for implicating novel gene ensembles in cellular mechanisms of health and disease. The most popular platform for genome-wide expression profiling is the Affymetrix GeneChip. However, its selection of probes relied on earlier genome and transcriptome annotation which is significantly different from current knowledge. The resultant informatics problems have a profound impact on analysis and interpretation the data. Here, we address these critical issues and offer a solution. We identified several classes of problems at the individual probe level in the existing annotation, under the assumption that current genome and transcriptome databases are more accurate than those used for GeneChip design. We then reorganized probes on more than a dozen popular GeneChips into gene-, transcript- and exon-specific probe sets in light of up-to-date genome, cDNA/EST clustering and single nucleotide polymorphism information. Comparing analysis results between the original and the redefined probe sets reveals approximately 30-50% discrepancy in the genes previously identified as differentially expressed, regardless of analysis method. Our results demonstrate that the original Affymetrix probe set definitions are inaccurate, and many conclusions derived from past GeneChip analyses may be significantly flawed. It will be beneficial to re-analyze existing GeneChip data with updated probe set definitions.
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Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197
Model-based analysis of oligonucleotide arrays: Expression index computation and outlier detection.
Li, C., & Wong, W. H. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.1.31 · Cited by 3,133
Harbig, J. (2005) · Nucleic Acids Research · doi:10.1093/nar/gni027 · Cited by 141
Cited by
Aran, D., Looney, A. P., Liu, L., Wu, E., Fong, V., Hsu, A., Chak, S., Naikawadi, R. P., Wolters, P. J., Abate, A. R., et al. (2019) · Nature Immunology · doi:10.1038/s41590-018-0276-y · Cited by 4,984
xCell: digitally portraying the tissue cellular heterogeneity landscape
Aran, D., Hu, Z., & Butte, A. J. (2017) · Genome Biology · doi:10.1186/s13059-017-1349-1 · Cited by 4,397
Clonal hematopoiesis associated with TET2 deficiency accelerates atherosclerosis development in mice
Fuster, J. J., MacLauchlan, S., Zuriaga, M. A., Polackal, M. N., Ostriker, A. C., Chakraborty, R., Wu, C.-L., Sano, S., Muralidharan, S., Rius, C., et al. (2017) · Science · doi:10.1126/science.aag1381 · Cited by 1,536
GAGE: generally applicable gene set enrichment for pathway analysis
Luo, W., Friedman, M. S., Shedden, K., Hankenson, K. D., & Woolf, P. J. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-161 · Cited by 1,333
Genome-wide analysis of estrogen receptor binding sites
Carroll, J. S., Meyer, C. A., Song, J., Li, W., Geistlinger, T. R., Eeckhoute, J., Brodsky, A. S., Keeton, E. K., Fertuck, K. C., Hall, G. F., et al. (2006) · Nature Genetics · doi:10.1038/ng1901 · Cited by 1,377
Metadata
- Authors
- Dai, M.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-11-27
- Volume
- 33
- Issue
- 20
- Pages
- e175-e175
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2135827569
- Cited by
- 1,797
- References
- 3
- FWCI
- 19.48
- Type
- journal article
- Language
- en
- Open access
- gold
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