MOST: detecting cancer differential gene expression.

  title={MOST: detecting cancer differential gene expression.},
  author={Heng Lian},
  volume={9 3},
We propose a new statistics for the detection of differentially expressed genes when the genes are activated only in a subset of the samples. Statistics designed for this unconventional circumstance has proved to be valuable for most cancer studies, where oncogenes are activated for a small number of disease samples. Previous efforts made in this direction include cancer outlier profile analysis (Tomlins and others, 2005), outlier sum (Tibshirani and Hastie, 2007), and outlier robust t… CONTINUE READING

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