makeDesign {TOAST} | R Documentation

## Generate design matrix from input phenotypes and proportions.

### Description

This function generate design matrix and make preparations for following fitModel and csTest.

### Usage

    makeDesign(design, Prop)

### Arguments

`design` | A N by P phenotype matrix, with rows as samples and columns as phenotypes (e.g. age, gender, disease, etc.).
`Prop` | A N by K proportion matrix, with rows as samples and columns as cell types

### Value

`design_matrix` | A comprehensive design matrix incorporated phenotype and proportion information.
`Prop` | The input proportion matrix.
`design` | The input design/phenotype matrix.
`all_coefs` | The names of all phenotypes.
`all_cell_types` | The names of all cell types.
`formula` | The formula of the tested model, including all phenotypes, cell types and interaction terms.

### Author(s)

Ziyi Li <ziyi.li@emory.edu>

### References

Ziyi Li, Zhijin Wu, Peng Jin, Hao Wu. "Dissecting differential signals in high-throughput data from complex tissues."

### Examples

    N = 300 # simulation a dataset with 300 samples
    K = 3 # 3 cell types

    ### simulate proportion matrix
    Prop = matrix(runif(N*K, 10,60), ncol=K)
    Prop = sweep(Prop, 1, rowSums(Prop), FUN="/")
    colnames(Prop) = c("Neuron", "Astrocyte", "Microglia")

    ### simulate phenotype names
    design <- data.frame(disease=factor(sample(0:1, size = N,replace=TRUE)),
                         age=round(runif(N, 30,50)),
                         race=factor(sample(1:3, size = N,replace=TRUE)))
    Design_out <- makeDesign(design, Prop)

[Package TOAST version 1.4.0 Index]