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The FMT method computes posterior residual variances to be used in the denominator of a moderated t-statistic from a linear model analysis of gene expression data. It is an extension of the moderated t-statistic originally proposed by Smyth (2004) <doi:10.2202/1544-6115.1027>. LOESS local regression and empirical Bayesian method are used to estimate gene specific prior degrees of freedom and prior variance based on average gene intensity levels. The posterior residual variance in the denominator is a weighted average of prior and residual variance and the weights are prior degrees of freedom and residual variance degrees of freedom. The degrees of freedom of the moderated t-statistic is simply the sum of prior and residual variance degrees of freedom.
| Version: | 2.0 |
| Depends: | R (≥ 3.5.0), limma |
| Published: | 2022-09-05 |
| Author: | Lianbo Yu [aut, cre] |
| Maintainer: | Lianbo Yu <Lianbo.Yu at osumc.edu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | fmt results |
| Reference manual: | fmt.pdf |
| Package source: | fmt_2.0.tar.gz |
| Windows binaries: | r-devel: fmt_2.0.zip, r-release: fmt_2.0.zip, r-oldrel: fmt_2.0.zip |
| macOS binaries: | r-release (arm64): fmt_2.0.tgz, r-oldrel (arm64): fmt_2.0.tgz, r-release (x86_64): fmt_2.0.tgz, r-oldrel (x86_64): fmt_2.0.tgz |
| Old sources: | fmt archive |
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