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Detecting, correcting, and preventing the batch effects in multi-site data, with a focus on gene expression Microarrays
DownloadSpring 2014
Gene expression microarrays are widely used to better understand the complex biological mechanisms inside cells. One of the main obstacles of applying statistical learning algorithms to microarray data is the large gap between the number of features (p) and the number of available instances (n),...
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Estimating the Overlap of Top Instances in Lists Ranked by Correlation to Label
Spring 2012
Recent advances in high-throughput technologies, such as genome-wide SNP analysis and microar- ray gene expression profiling, have led to a multitude of ranked lists, where the features (SNPs, genes) are sorted based on their individual correlation with a phenotype. Multiple reviews have shown...
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