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This paper breaks new ground in normalization and clustering methods for highly replicated temporal microarray data.
Normalization and clustering were performed in GeneSpring software (Agilent Technologies).
Multi-array normalization and clustering analysis were performed using a hierarchical method, with an average linkage and Euclidean distance metric.
The hybridization signal was subjected to normalization and clustering by using open-source R (ver. 2.1.1) packages and S-Plus (Insightful, WA).
(A ) Normalization and clustering were performed according to the procedures described for Figure 3C legend.
(XLSX 62 kb) Additional file 12: Comprises of additional details of the methods, including the options and parameters of the tools used for processing of the reads, known miRNA expression profile generation, normalization and clustering and novel miRNA prediction pipeline.
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Though other inter-platform normalization methods and clustering methods were tested (z-score, quantile normalization), we found that only by using a common reference sample and transforming single intensity data into a log ratio enabled us to overcome the platform-dependent bias and observe cross-platform cell line-specific clusters.
This provided a high confidence dataset of 434 chips on which a final background correction, normalization, and cluster analysis for all the data were performed.
Then data normalization by a normalization factor and clustering was performed based on mean intensity for inter-array comparison.
In the particular case presented in this work, this layer contains agents for normalization and segmentation, knowledge extraction, and clustering.
The raw scanned image files were processed by using data normalization, quality assurance and control, filtering, and clustering.
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