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- W2406298418 abstract "Recently lots of attention has been paid to gene set analysis for identifying differentially expressed gene-sets between two sample groups. Unlike earlier approaches, the gene set analysis enables us to find significant gene-sets along with their functional characteristics. For this reason, various novel approaches have been suggested lately for gene set analysis. As one of such, PAGE is a parametric approach that employs average difference (AD) as an expression metric to quantify expression differences between two sample groups and assumes that the distribution of gene scores is normal. This approach is preferred to non-parametric approach because of more effective performance. However, the metric AD does not reflect either gene expression intensities or variances over samples in calculating gene scores. Thus, in this paper, we investigate the usefulness of several other expression metrics for parametric gene-set analysis, which consider actual expression intensities of genes or their expression variances over samples. For this purpose, we examined three expression metrics, WAD (weighted average difference), FC (Fisher's criterion), and Abs_SNR (Absolute value of signal-to-noise ratio) for parametric gene set analysis and evaluated their experimental results." @default.
- W2406298418 created "2016-06-24" @default.
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- W2406298418 date "2010-01-01" @default.
- W2406298418 modified "2023-09-26" @default.
- W2406298418 title "A Comparative Study of Parametric Methods for Significant Gene Set Identification Depending on Various Expression Metrics" @default.
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