Pakiet: r-bioc-qusage (2.32.0-1)

[ Pakiet źródłowy: r-bioc-qusage  ]

qusage: Quantitative Set Analysis for Gene Expression

This package is an implementation the Quantitative Set Analysis for Gene Expression (QuSAGE) method described in (Yaari G. et al, Nucl Acids Res, 2013). This is a novel Gene Set Enrichment-type test, which is designed to provide a faster, more accurate, and easier to understand test for gene expression studies. qusage accounts for inter-gene correlations using the Variance Inflation Factor technique proposed by Wu et al. (Nucleic Acids Res, 2012). In addition, rather than simply evaluating the deviation from a null hypothesis with a single number (a P value), qusage quantifies gene set activity with a complete probability density function (PDF). From this PDF, P values and confidence intervals can be easily extracted. Preserving the PDF also allows for post-hoc analysis (e.g., pair-wise comparisons of gene set activity) while maintaining statistical traceability. Finally, while qusage is compatible with individual gene statistics from existing methods (e.g., LIMMA), a Welch-based method is implemented that is shown to improve specificity. For questions, contact Chris Bolen ([e-mail]) or Steven Kleinstein ([e-mail])

Inne pakiety związane z r-bioc-qusage

• dep: r-api-4.0

  pakiet wirtualny udostępniany przez r-base-core

• dep: r-api-bioc-3.16

  pakiet wirtualny udostępniany przez r-bioc-biocgenerics

• dep: r-base-core (>= 4.2.2.20221110-1)

  GNU R core of statistical computation and graphics system

• dep: r-bioc-biobase

  base functions for Bioconductor

• dep: r-bioc-limma (>= 3.14)

  linear models for microarray data

• dep: r-cran-emmeans

  GNU R estimated marginal means, aka least-squares means

• dep: r-cran-fftw

  GNU R fast FFT and DCT Based on the FFTW Library

• dep: r-cran-nlme

  GNU R package for (non-)linear mixed effects models

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