Abstract

Identification of gene structures is key to genome annotation, and analysis of alternative RNA processing is critical to understand transcriptome diversity and genome coding capacity. Tiling microarray has become an important tool for genome-wide analysis of gene expression due to its high resolution, high density and throughput. However, for the huge volume of data and limited probe design options, analysis of tiling microarray data is neither easy nor effective. PROBER, a tool for integrated analysis of massive tiling microarray data, is developed to identify gene structures and analyze differential gene expression. In PROBER, after normalization of microarray data, structural change model is used to identify gene structures. T-Test, wavelet and other methods are then adopted to analyze differential expression of genes under different conditions. By combining tiling microarray technology and applying computer recognition models and algorithms, applications of PROBER in gene annotation and alternative RNA processing are demonstrated.

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