Computes gene wise t-statistic with variance stabilised by adding the 90th percentile.

1 |

`X` |
Gene expression matrix with samples as rows and genes as columns |

`y` |
Optional vector of 0/1 indicating sample phenotype |

Computes a gene wise t-statistic with variance stabilised by adding the 90th percentile of all the genes' standard deviations to a gene's standard devitation (Efron et al. 2001). If y is given, a two-sample test is performed, otherwise a one-sample test is performed. For a two-sample t-test the approach of Pan et al. (2003) is used.

`tS ` |
Vector with one smoothed t-value for each gene |

Guro D\orum

Efron, B., Tibshirani, R., Storey, J. D. and Tusher, V. (2001)
Empirical Bayes analysis of a microarray experiment,
*J Amer Statist Assoc*,
**96**, 1151-1160.

Pan,W., Lin,J. and Le,C.T. (2003)
A mixture model approach to detecting differentially expressed genes with microarray data,
*Funct Integr Genomics*,
**3**, 117<96>124.

1 2 3 | ```
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
``` |

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