Auburn et al. SimArray: a user-friendly and user-configurable microarray design tool. BMC Bioinformatics 2006 Spatial bias heat maps Spatial variation is observed even in the best laboratories [1-5]. Spatial bias can be plotted in form of heat maps. The following heat maps were selected at random, and show six dual-channel microarrays. The microarrays were printed and hybridised according to the protocols given by the UK Drosophila microarray facility web site [6]. The x/y-coordinates represent location on the microarray, whilst the colouring and contours indicate the difference between the Cy5 and Cy3 channels. These six examples show that spot location has a direct impact on the measured differential gene expression ratios and hence supports the need for randomisation of the spot layout to facilitate correction of spatial biases by normalisation [7-11]. -1- Auburn et al. SimArray: a user-friendly and user-configurable microarray design tool. BMC Bioinformatics 2006 First example Two patches of high gene expression ratios towards the centre of the array and decreased ratios towards the edges, especially the right edge. The top and bottom are roughly equivalent to the central region. -2- Auburn et al. SimArray: a user-friendly and user-configurable microarray design tool. BMC Bioinformatics 2006 Second example Gradual increase in the measured gene expression ratios from bottom-to-top. The rate of increase varies between the left and right, leading to a second gradient running across the centre of the array from right-to-left. -3- Auburn et al. SimArray: a user-friendly and user-configurable microarray design tool. BMC Bioinformatics 2006 Third example Low gene expression ratios at the centre, top and bottom of the array. Higher ratios towards the left and right edges. -4- Auburn et al. SimArray: a user-friendly and user-configurable microarray design tool. BMC Bioinformatics 2006 Fourth example Low ratios at the left and right edges that appear to increase towards the centre and then again at the top of the microarray. -5- Auburn et al. SimArray: a user-friendly and user-configurable microarray design tool. BMC Bioinformatics 2006 Fifth example High ratios at the bottom and top-left corner of the array, low ratios for one patch on the left edge and the entire top-right corner. -6- Auburn et al. SimArray: a user-friendly and user-configurable microarray design tool. BMC Bioinformatics 2006 Sixth example Reasonably even ratios across most of the microarray, but with slightly higher ratios in the top-left corner. -7- Auburn et al. SimArray: a user-friendly and user-configurable microarray design tool. BMC Bioinformatics 2006 References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. Wernisch L, Kendall SL, Soneji S, Wietzorrek A, Parish T, Hinds J, Butcher PD, Stoker NG: Analysis of whole-genome microarray replicates using mixed models. Bioinformatics 2003, 19(1):53-61. Qian J, Kluger Y, Yu H, Gerstein M: Identification and correction of spurious spatial correlations in microarray data. Biotechniques 2003, 35(1):42-44, 46, 48. Yang YH, Buckley MJ, Dudoit S, Speed TP: Comparison of methods for image analysis on cDNA microarray data. J Comp Graph Stat 2002, 11(1):108-136. Yang YH, Dudoit S, Luu P, Lin DM, Peng V, Ngai J, Speed TP: Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res 2002, 30(4):e15. Futschik ME, Crompton T: OLIN: optimized normalization, visualization and quality testing of two-channel microarray data. Bioinformatics 2005, 21(8):1724-1726. FlyChip: the UK Drosophila microarray facility.[ http://www.flychip.org.uk/ ]. Kreil DP, Russell RR: There is no silver bullet--a guide to low-level data transforms and normalisation methods for microarray data. Brief Bioinform 2005, 6(1):86-97. Kerr MK, Churchill GA: Statistical design and the analysis of gene expression microarray data. Genet Res 2001, 77(2):123-128. Churchill GA: Fundamentals of experimental design for cDNA microarrays. Nat Genet 2002, 32 Suppl:490-495. Brodsky L, Leontovich A, Shtutman M, Feinstein E: Identification and handling of artifactual gene expression profiles emerging in microarray hybridization experiments. Nucleic Acids Res 2004, 32(4):e46. Le Meur N, Lamirault G, Bihouee A, Steenman M, Bedrine-Ferran H, Teusan R, Ramstein G, Leger JJ: A dynamic, web-accessible resource to process raw microarray scan data into consolidated gene expression values: importance of replication. Nucleic Acids Res 2004, 32(18):5349-5358. -8-