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acde (version 1.2.0)

Artificial Components Detection of Differentially Expressed Genes

Description

This package provides a multivariate inferential analysis method for detecting differentially expressed genes in gene expression data. It uses artificial components, close to the data's principal components but with an exact interpretation in terms of differential genetic expression, to identify differentially expressed genes while controlling the false discovery rate (FDR). The methods on this package are described in the vignette or in the article 'Multivariate Method for Inferential Identification of Differentially Expressed Genes in Gene Expression Experiments' by J. P. Acosta, L. Lopez-Kleine and S. Restrepo (2015, pending publication).

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Version

Version

1.2.0

License

GPL-3

Maintainer

Juan Pablo Acosta

Last Published

February 15th, 2017

Functions in acde (1.2.0)

plot.STP

Plot Method for Single Time Point Analysis
fdr

False Discovery Rate Computation
ac

Artificial Components for Gene Expression Data
bcaFDR

BCa Confidence Upper Bound for the FDR
plot.TC

Plot Method for Time Course Analysis
print.TC

Print Method for Time Course Analysis
tc

Time Course Analysis for Detecting Differentially Expressed Genes
qval

Q-Values Computation
stp

Single Time Point Analysis for Detecting Differentially Expressed Genes
phytophthora

Gene Expression Data for Tomato Plants Inoculated with Phytophthora infestans
acde-package

Artificial Components Detection of Differentially Expressed Genes
print.STP

Print Method for Single Time Point Analysis