Package: fmt 2.0

Lianbo Yu

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.

Authors:Lianbo Yu [aut, cre]

fmt_2.0.tar.gz
fmt_2.0.zip(r-4.7-any)fmt_2.0.zip(r-4.6-any)
fmt_2.0.tar.gz(r-4.7-any)fmt_2.0.tar.gz(r-4.6-any)
fmt_2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
fmt/json (API)

# Install 'fmt' in R:
install.packages('fmt', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.03 score 106 scripts 315 downloads 2 exports 2 dependencies

Last updated from:0392fa5b9a. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK92
source / vignettesOK139
linux-releaseOK91
windows-develOK61
windows-releaseOK63
wasm-releaseOK98

Exports:fmtplotFMT

Dependencies:limmastatmod