fmt: Variance Estimation of FMT Method (Fully Moderated T-Statistic)

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

Documentation:

Reference manual: fmt.pdf

Downloads:

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
Old sources: fmt archive

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