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DNA 마이크로어레이 자료의 PRINT-TIP별 표준화(NORMALIZATION) 방법

Print-tip Normalization for DNA Microarray Data

  • 이성곤 (서울대학교 자연과학대학 통계학과) ;
  • 박태성 (서울대학교 자연과학대학 통계학과) ;
  • 강성현 (서울대학교 자연과학대학 통계학과) ;
  • 이승연 (세종대학교 응용수학과) ;
  • 이용성 (한양대학교 생화학교실)
  • Yi Sung-Gon (Department of Statistics, Seoul National University) ;
  • Park Taesung (Department of Statistics, Seoul National University) ;
  • Kang Sung Hyun (Department of Statistics, Seoul National University) ;
  • Lee Seung-Yeaun (Department of Applied Mathematics, Sejong University) ;
  • Lee Yang Sung (Department of Biochemistry, Hanyang University)
  • 발행 : 2005.03.01

초록

DNA마이크로어레이 기술은 수천 개 또는 수만 개의 유전자의 발현을 동시에 탐색할 수 있는 새로운 과학 기술이다. 표준화(normalization)는 마이크로어레이 실험에서 다양한 원인에 의해 발생하는 잡음(noise)을 줄이거나 제거하는 과정을 나타낸다. print-tip의 변동은 잡음의 주요 요인으로 인지되어 왔다. 본 논문에서는 잡음의 주요 발생요인이 되는 print-tip의 변동을 조절하기 위한 print-tip 표준화 작업에 대한 객관적인 비교 및 그 타당성 평가를 하였다. 먼저 그동안 제안된 여러 표준화 방법들 중에서 가장 널리 사용되고 있는 방법들을 정리해서 소개한 후에, 잡음이 많이 포함된 실제 cDNA 실험자료를 이용하여 각 표준화 방법의 특성을 비교해 보았다. 또한 실험자료와 유사한 모의분포를 생성한 후에 print-tip 표준화 작업에 대한 체계적인 비교를 해 보았다.

DNA microarray experiments allow us to study expression of thousands of genes simultaneously, Normalization is a process for removing noises occurred during the microarray experiment, Print-tip is regarded as one main sources of noises, In this paper, we review normalization methods most commonly used in the microarray experiments, Especially, we investigate the effects of print-tips through simulated data sets.

키워드

참고문헌

  1. Chen, Y., Dougherty, E.R., and Bittner, M.L. (1997). Ratio-based decisions and the quantitative analysis of cDNA microarray images, Journal of Biomedical Optics, 2, 364-374 https://doi.org/10.1117/12.281504
  2. Chen Y.J., Kodell, R., Sistare. F., Thompson, KL, Morris, S., and Chen, J.J. (2003). Normalization methods for analysis of microarray gene-expression data, Journal of Biopharmceutical Statistics, 13, 57-74 https://doi.org/10.1081/BIP-120017726
  3. Cleveland (1979). Robust locally weighted regression and smoothing scatterplots, Journal of the American Statistical Association, 74, 829-836 https://doi.org/10.2307/2286407
  4. Johe, K.K., Hazel, T.G., Muller, T., Dugich-Djordjevic, M.M., and McKay, R.D. (1996). Single factors direct the differentiation of stem cells from the fetal and adult central nervous system, Genes f3 Development, 10, 3129-3140 https://doi.org/10.1101/gad.10.24.3129
  5. Kepler T.B., Crosby L., and Morgan K.T. (2002). Normalization and analysis of DNA micro array data by self-consistency and local regression, Genome Biology, 3, research 0037.1-0037.12
  6. Kerr, M.K, Martin, M., and Churchill, G.A. (2000). Analysis of variance for gene expression microarray data, Journal of Computational Biology, 7, 819-837 https://doi.org/10.1089/10665270050514954
  7. Kerr, M.K., Afshari, C.A., Bennett, J., Bushel, P., Martinez, J., Walker, N., and Churchill, G.A. (2001). Statistical analysis of a gene expression microarray experiment with replication, Statistica Sinica, 12, 203-217
  8. Park, T., Yi, S.-G., Kang, S.-H., Lee, S., Lee, Y.-S., and Simon, R. (2003). Evaluation of normalization methods for microarray data, BMC Bioinformatics, 4, 33
  9. Quackenbush J. (2001). Computational analysis of microarray data, Nature Review Genetics, 2, 418-427 https://doi.org/10.1038/35076576
  10. Quackenbush J. (2002). Microarray data normalization and transformation, Nature Genetics, 32, Suppl:496-501 https://doi.org/10.1038/ng1032
  11. Tseng, G.C, Oh, M.K., Rohlin, L., Liao, J.C., and Wong, W.H. (2001). Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects, Nucleic Acids Research, 29, 2549-2557 https://doi.org/10.1093/nar/29.12.2549
  12. Yang, Y.H., Dudoit, S., Luu, D.M, Peng, V., Ngai, J., and Speed, T.P. (2002). Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide sysytematic variation, Nucleic Acids Research, 30, e15
  13. Wang, Y., Lu, J., Lee, R., Gu, Z., and Clarke, R. (2002). Iterative normalization of cDNA microarray data, IEEE Transactions on Information Technology Biomedicine, 6, 29-37 https://doi.org/10.1109/4233.992159
  14. Wolfinger, RD., Gibson, G., Wolfinger, E.D., Bennett, L., Hamadeh, H., Bushel, P., Afshari, C., and Paules, RS. (2001). Assessing gene significance from cDNA microarray expression data via mixed models, Journal of Computational Biology, 8, 625-637 https://doi.org/10.1089/106652701753307520
  15. Workman C., Jensen L. J., Jarmer H., Berka R, Gautier L., Nielser H. B., Saxild H. H., Nielsen C., Brunak S., and Knudsen S. (2002). A new non-linear normalization method for reducing variability in DNA microarrayexperiments, Genome Biology, 3, research0048.1-research0048.16