- About this Journal ·
- Abstracting and Indexing ·
- Aims and Scope ·
- Article Processing Charges ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Recently Accepted Articles ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
Advances in Bioinformatics
Volume 2013 (2013), Article ID 167915, 9 pages
Correction of Spatial Bias in Oligonucleotide Array Data
1Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, C.P. 6128, Succursale Centre-Ville, Montréal, QC, Canada H3C 3J7
2Department of Computer Science and Operations Research, Université de Montréal, C.P. 6128, Succursale Centre-Ville, Montréal, QC, Canada H3C 3J7
Received 6 July 2012; Accepted 2 February 2013
Academic Editor: Tatsuya Akutsu
Copyright © 2013 Philippe Serhal and Sébastien Lemieux. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- M. Schena, D. Shalon, R. W. Davis, and P. O. Brown, “Quantitative monitoring of gene expression patterns with a complementary DNA microarray,” Science, vol. 270, no. 5235, pp. 467–470, 1995.
- R. Edgar, M. Domrachev, and A. E. Lash, “Gene Expression Omnibus: NCBI gene expression and hybridization array data repository,” Nucleic Acids Research, vol. 30, no. 1, pp. 207–210, 2002.
- D. J. Lockhart, H. Dong, M. C. Byrne et al., “Expression monitoring by hybridization to high-density oligonucleotide arrays,” Nature Biotechnology, vol. 14, no. 13, pp. 1675–1680, 1996.
- D. W. Selinger, K. J. Cheung, R. Mei et al., “RNA expression analysis using a 30 base pair resolution Escherichia coli genome array,” Nature Biotechnology, vol. 18, no. 12, pp. 1262–1268, 2000.
- A. J. Hartemink, D. K. Gifford, T. S. Jaakkola, and R. A. Young, “Maximum likelihood estimation of optimal scaling factors for expression array normalization,” Microarrays: Optical Technologies and Informatics, vol. 2, no. 23, pp. 132–140, 2001.
- L. M. Cope, R. A. Irizarry, H. A. Jaffee, Z. Wu, and T. P. Speed, “A benchmark for Affymetrix GeneChip expression measures,” Bioinformatics, vol. 20, no. 3, pp. 323–331, 2004.
- R. Gentleman, Bioinformatics and Computational Biology Solutions Using R and Bioconductor, Springer Science and Business Media, New York, NY, USA, 2005.
- F. Naef and M. O. Magnasco, “Solving the riddle of the bright mismatches: labeling and effective binding in oligonucleotide arrays,” Physical Review E, vol. 68, no. 1, part 1, Article ID 011906, 2003.
- Z. Wu and R. A. Irizarry, “Stochastic models inspired by hybridization theory for short oligonucleotide arrays,” Journal of Computational Biology, vol. 12, no. 6, pp. 882–893, 2005.
- M. Reimers and J. N. Weinstein, “Quality assessment of microarrays: visualization of spatial artifacts and quantitation of regional biases,” BMC Bioinformatics, vol. 6, article 166, 2005.
- M. Suárez-Fariñas, A. Haider, and K. M. Wittkowski, “"Harshlighting" small blemishes on microarrays,” BMC Bioinformatics, vol. 6, article 65, 2005.
- G. J. G. Upton and J. C. Lloyd, “Oligonucleotide arrays: information from replication and spatial structure,” Bioinformatics, vol. 21, no. 22, pp. 4162–4168, 2005.
- J. M. Arteaga-Salas, A. P. Harrison, and G. J. G. Upton, “Reducing spatial flaws in oligonucleotide arrays by using neighborhood information,” Statistical Applications in Genetics and Molecular Biology, vol. 7, no. 1, article 29, 2008.
- W. B. Langdon, G. J. Upton, R. da Silva Camargo, and A. P. Harrison, “A survey of spatial defects in Homo Sapiens Affymetrix GeneChips,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 7, no. 4, pp. 647–653, 2010.
- R. Z. Gharaibeh, A. A. Fodor, and C. J. Gibas, “Software note: using probe secondary structure information to enhance Affymetrix GeneChip background estimates,” Computational Biology and Chemistry, vol. 31, no. 2, pp. 92–98, 2007.
- V. G. Ratushna, J. W. Weller, and C. J. Gibas, “Secondary structure in the target as a confounding factor in synthetic oligomer microarray design,” BMC Genomics, vol. 6, article 31, 2005.
- H. Wei, P. F. Kuan, S. Tian et al., “A study of the relationships between oligonucleotide properties and hybridization signal intensities from NimbleGen microarray datasets,” Nucleic Acids Research, vol. 36, no. 9, pp. 2926–2938, 2008.
- M. P. Samanta, W. Tongprasit, H. Sethi, C. Chin, and V. Stolc, “Global identification of noncoding RNAs in Saccharomyces cerevisiae by modulating an essential RNA processing pathway,” Proceedings of the National Academy of Sciences of the United States of America, vol. 103, no. 11, pp. 4192–4197, 2006.
- G. J. G. Upton, O. Sanchez-Graillet, J. Rowsell et al., “On the causes of outliers in Affymetrix GeneChip data,” Briefings in Functional Genomics and Proteomics, vol. 8, no. 3, pp. 199–212, 2009.
- A. A. Ahmed, M. Vias, N. G. Iyer, C. Caldas, and J. D. Brenton, “Microarray segmentation methods significantly influence data precision,” Nucleic Acids Research, vol. 32, no. 5, article e50, 2004.
- J. T. Leek and J. D. Storey, “Capturing heterogeneity in gene expression studies by surrogate variable analysis,” PLoS Genetics, vol. 3, no. 9, pp. 1724–1735, 2007.
- R. A. Irizarry, B. Hobbs, F. Collin et al., “Exploration, normalization, and summaries of high density oligonucleotide array probe level data,” Biostatistics, vol. 4, no. 2, pp. 249–264, 2003.
- F. Naef, D. A. Lim, N. Patil, and M. Magnasco, “DNA hybridization to mismatched templates: a chip study,” Physical Review E, vol. 65, no. 4, part 1, Article ID 040902, 2002.
- Affymetrix, “GeneChip Gene 1.0 ST Array System,” Santa Clara, Calif, USA, 2007.
- Y. H. Yang, S. Dudoit, P. Luu, and T. P. Speed, “Normalization for cDNA microarray data,” Microarrays: Optical Technologies and Informatics, vol. 2, no. 23, pp. 141–152, 2001.
- S. Dudoit, Y. H. Yang, M. J. Callow, and T. P. Speed, “Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments,” Statistica Sinica, vol. 12, no. 1, pp. 111–139, 2002.
- B. M. Bolstad, R. A. Irizarry, M. Astrand, and T. P. Speed, “A comparison of normalization methods for high density oligonucleotide array data based on variance and bias,” Bioinformatics, vol. 19, no. 2, pp. 185–193, 2003.
- J. A. Berger, S. Hautaniemi, A. Järvinen, H. Edgren, S. K. Mitra, and J. Astola, “Optimized LOWESS normalization parameter selection for DNA microarray data,” BMC Bioinformatics, vol. 5, article 194, 2004.
- M. E. Ritchie, J. Silver, A. Oshlack et al., “A comparison of background correction methods for two-colour microarrays,” Bioinformatics, vol. 23, no. 20, pp. 2700–2707, 2007.
- S. L. Carter, A. C. Eklund, B. H. Mecham, I. S. Kohane, and Z. Szallasi, “Redefinition of Affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements,” BMC Bioinformatics, vol. 6, article 107, 2005.
- C. Wu, R. Carta, and Zhang, “Sequence dependence of cross-hybridization on short oligo microarrays,” Nucleic Acids Research, vol. 33, no. 9, p. e84, 2005.
- H. Binder, J. Brücker, and C. J. Burden, “Nonspecific hybridization scaling of microarray expression estimates: a physicochemical approach for chip-to-chip normalization,” Journal of Physical Chemistry B, vol. 113, no. 9, pp. 2874–2895, 2009.
- Y. H. Yang, S. Dudoit, P. Luu et al., “Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation,” Nucleic Acids Research, vol. 30, no. 4, p. e15, 2002.
- C. Workman, L. J. Jensen, H. Jarmer et al., “A new non-linear normalization method for reducing variability in DNA microarray experiments,” Genome Biology, vol. 3, no. 9, research0048, 2002.
- C. Colantuoni, G. Henry, S. Zeger, and J. Pevsner, “Local mean normalization of microarray element signal intensities across an array surface: quality control and correction of spatially systematic artifacts,” BioTechniques, vol. 32, no. 6, pp. 1316–1320, 2002.
- D. L. Wilson, M. J. Buckley, C. A. Helliwell, and I. W. Wilson, “New normalization methods for cDNA microarray data,” Bioinformatics, vol. 19, no. 11, pp. 1325–1332, 2003.
- D. Baird, P. Johnstone, and T. Wilson, “Normalization of microarray data using a spatial mixed model analysis which includes splines,” Bioinformatics, vol. 20, no. 17, pp. 3196–3205, 2004.
- A. L. Tarca, J. E. Cooke, and J. Mackay, “A robust neural networks approach for spatial and intensity-dependent normalization of cDNA microarray data,” Bioinformatics, vol. 21, no. 11, pp. 2674–2683, 2005.
- P. Neuvial, P. Hupé, I. Brito et al., “Spatial normalization of array-CGH data,” BMC Bioinformatics, vol. 7, article 264, 2006.
- H. S. Chai, T. M. Therneau, K. R. Bailey, and J. A. Kocher, “Spatial normalization improves the quality of genotype calling for Affymetrix SNP 6.0 arrays,” BMC Bioinformatics, vol. 11, article 356, 2010.
- J. M. Arteaga-Salas, H. Zuzan, W. B. Langdon, G. J. G. Upton, and A. P. Harrison, “An overview of image-processing methods for affymetrix genechips,” Briefings in Bioinformatics, vol. 9, no. 1, pp. 25–33, 2008.
- T. H. Stokes, R. A. Moffitt, J. H. Phan, and M. D. Wang, “Chip artifact CORRECTion (caCORRECT): a bioinformatics system for quality assurance of genomics and proteomics array data,” Annals of Biomedical Engineering, vol. 35, no. 6, pp. 1068–1080, 2007.
- R. A. Irizarry, Z. Wu, and H. A. Jaffee, “Comparison of Affymetrix GeneChip expression measures,” Bioinformatics, vol. 22, no. 7, pp. 789–794, 2006.
- N. O. Stitziel, B. G. Mar, J. Liang, and C. A. Westbrook, “Membrane-associated and secreted genes in breast cancer,” Cancer Research, vol. 64, no. 23, pp. 8682–8687, 2004.
- D. Magda, P. Lecane, R. A. Miller et al., “Motexafin gadolinium disrupts zinc metabolism in human cancer cell lines,” Cancer Research, vol. 65, no. 9, pp. 3837–3845, 2005.
- “Latin Square Data for Expression Algorithm Assessment,” http://www.affymetrix.com/support/technical/sample_data/datasets.affx.
- C. Cheng and L. M. Li, “Sub-array normalization subject to differentiation,” Nucleic Acids Research, vol. 33, no. 17, pp. 5565–5573, 2005.
- C. Li and W. H. Wong, “Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection,” Proceedings of the National Academy of Sciences of the United States of America, vol. 98, no. 1, pp. 31–36, 2001.
- B. Bolstad, J. Brettschneider, K. Simpson, L. Cope, R. Irizarry, and T. P. Speed, “Quality assessment of affymetrix GeneChip data,” in Bioinformatics and Computational Biology Using R and Bioconductor, R. Gentleman, V. Carey, W. Huber, R. Irizarry, and S. Dudoit, Eds., Springer, 2005.
- R. C. Geary, “The contiguity ratio and statistical mapping,” The Incorporated Statistician, vol. 5, no. 3, pp. 115–146, 1954.
- P. A. Moran, “Notes on continuous stochastic phenomena,” Biometrika, vol. 37, no. 1-2, pp. 17–23, 1950.
- Z. Wu, R. A. Irizarry, R. Gentleman, F. Martinez-Murillo, and F. Spencer, “A model-based background adjustment for oligonucleotide expression arrays,” Journal of the American Statistical Association, vol. 99, no. 468, pp. 909–917, 2004.
- B. M. Bolstad, Low-level analysis of high-density oligonucleotide array data: background, normalization and summarization [Ph.D. thesis in biostatistics], University of California, Berkeley, 2004.