ac {acde} | R Documentation

## Artificial Components for Gene Expression Data

### Description

Computes the artificial components for gene expression data between two conditions for a single time point.

### Usage

    ac(Z, design)

    ac2(Z, design)

### Arguments

`Z` | a numeric matrix or data.frame with n rows and p columns representing genes' expression levels. The rows of Z correspond to the genes in the experiment, and the columns correspond to the replicates. Treatment replicates are to the left, control replicates to the right.
`design` | a vector of length p with 1's for the treatment replicates and 2's for the control replicates (1, …, 1, 2, …, 2).

### Details

This function computes the artificial components of Z, based on the specified design vector. First, the function scales Z so that its columns have zero mean and unit variance. Then computation of the artificial components ψ[1] and ψ[2] is performed as ψ[1] = Zv[1], where v[1] = (1, … , 1) / sqrt(p), and ψ[2] = Zv[2], where v[2] = (1, … , 1, -1, … , -1 ) / sqrt(p*p[1]*(p-p[1])). Here, p[1] is the number of treatment replicates, and v[2] has p[1] positive and p-p[1] negative entries.

### Value

`ac` returns a matrix with the artificial components ψ[1] and ψ[2] in the columns.

`ac2` returns a matrix with the second artificial component ψ[2] in the only column.

### Author(s)

Juan Pablo Acosta (jpacostar@unal.edu.co).

### References

Acosta, J. P. (2015) Strategy for Multivariate Identification of Differentially Expressed Genes in Microarray Data. Unpublished MS thesis. Universidad Nacional de Colombia, Bogot\'a.

### Examples

    ## Computes the artificial components for the
    ## phitophthora infestans data at 60 hai.
    psi <- ac(phytophthora[[4]], c(rep(1,8), rep(2,8)))
    plot(x=psi[,1], y=psi[,2])

[Package acde version 1.10.0 Index]