@article {26629,
	title = {Reproducibility of gene expression across generations of Affymetrix microarrays},
	journal = {BMC BioinformaticsBMC BioinformaticsBMC Bioinformatics},
	volume = {4},
	year = {2003},
	note = {Nimgaonkar, AshishSanoudou, DespinaButte, Atul JHaslett, Judith NKunkel, Louis MBeggs, Alan HKohane, Isaac SengP01828-01A1/PHS HHS/NS40828/NS/NINDS NIH HHS/U01 HL066582/HL/NHLBI NIH HHS/P01 NS040828/NS/NINDS NIH HHS/R01 AR044345/AR/NIAMS NIH HHS/P50 NS040828/NS/NINDS NIH HHS/U01HL066582/HL/NHLBI NIH HHS/R01AR44345/AR/NIAMS NIH HHS/Comparative StudyResearch Support, Non-U.S. Gov{\textquoteright}tResearch Support, U.S. Gov{\textquoteright}t, P.H.S.Validation StudyEngland2003/06/26 05:00BMC Bioinformatics. 2003 Jun 25;4:27. doi: 10.1186/1471-2105-4-27. Epub 2003 Jun 25.},
	month = {Jun 25},
	pages = {27},
	abstract = {BACKGROUND: The development of large-scale gene expression profiling technologies is rapidly changing the norms of biological investigation. But the rapid pace of change itself presents challenges. Commercial microarrays are regularly modified to incorporate new genes and improved target sequences. Although the ability to compare datasets across generations is crucial for any long-term research project, to date no means to allow such comparisons have been developed. In this study the reproducibility of gene expression levels across two generations of Affymetrix GeneChips (HuGeneFL and HG-U95A) was measured. RESULTS: Correlation coefficients were computed for gene expression values across chip generations based on different measures of similarity. Comparing the absolute calls assigned to the individual probe sets across the generations found them to be largely unchanged. CONCLUSION: We show that experimental replicates are highly reproducible, but that reproducibility across generations depends on the degree of similarity of the probe sets and the expression level of the corresponding transcript.},
	keywords = {Analysis/instrumentation/*methods/standards/statistics \& numerical data, Calibration, Computational Biology/instrumentation/methods/standards/statistics \& numerical, data, DNA, Complementary/analysis/genetics, Gene Expression Profiling/instrumentation/*methods/standards/statistics \&, Gene Expression Regulation/genetics, Humans, Muscle, Skeletal/chemistry/cytology, numerical data, Oligonucleotide Array Sequence, RNA Probes/genetics/standards, RNA, Complementary/analysis, RNA/analysis/genetics/standards, Statistical Distributions},
	isbn = {1471-2105 (Electronic)1471-2105 (Linking)},
	author = {Nimgaonkar, A. and Sanoudou, D. and Butte, A. J. and Haslett, J. N. and Kunkel, L. M. and Beggs, A. H. and Kohane, I. S.}
}
