CCMB Seminar Series Lecture
Abstract: The DNA microarray technology has been widely used in measuring gene expression levels in biomedical research. The potential ability of monitoring tens of thousands of genes simultaneously makes the microarray approach an efficient tool. However, the raw measurements are noisy. The data is a combination of specific binding and background noise. A considerable proportion of genese appear constantly expressed because the variation in signal is small and seemingly within the variation of background noise alone. The dynamic range of the gene expression level is thus limited to highly expressed genes. This is a crucial limit because often more than half of the genes in an experiment do not reach the level that differential expression can be reliably detected. Our previous work has shown that probes have sequence specific background levels and probe specific background adjustment can improve the dynamic range. Since large number of observations on the same probe is usually not available in a single study, information is borrowed across probes within each sample to estimate the probe specific background. The accumulation of microarray data in public data depository has enabled us to approach the problem from a different angle. With a large number of samples, we now observe data on the same probe across a large variety of experimental conditions. We start with a database of human gene expression arrays of 500 samples. Based on the expression profile on each gene across experiemtns, we evaluate each probe's tendency to non-specific binding and ability to track target expression variation. We demonstrate further extension of the dynamic range for gene expression measures.
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