https://github.com/csoneson/exploremodelmatrix

Explore design matrices interactively with R/Shiny
https://github.com/csoneson/exploremodelmatrix

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Explore design matrices interactively with R/Shiny

• Host: GitHub
• URL: https://github.com/csoneson/exploremodelmatrix
• Owner: csoneson
• License: other
• Created: 2019-07-06T19:32:33.000Z (over 5 years ago)
• Default Branch: devel
• Last Pushed: 2024-12-21T16:19:42.000Z (18 days ago)
• Last Synced: 2024-12-30T22:10:03.651Z (8 days ago)
• Language: R
• Homepage: https://csoneson.github.io/ExploreModelMatrix/
• Size: 7.69 MB
• Stars: 36
• Watchers: 7
• Forks: 2
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS.md
  • License: LICENSE

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README

        


# ExploreModelMatrix

[![Codecov.io coverage status](https://codecov.io/github/csoneson/ExploreModelMatrix/coverage.svg?branch=master)](https://codecov.io/github/csoneson/ExploreModelMatrix)

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`ExploreModelMatrix` is a small R package that lets the user interactively

explore a design matrix as generated by the `model.matrix()` R function. 

In particular, given a table with sample information

and a design formula, `ExploreModelMatrix` illustrates the fitted values 

from a general linear model (or, more generally, the value of the linear 

predictor of a generalized linear model) for each combination of

input variables, simplifying understanding and generation of contrasts. A 

number of other visualizations are also included in the interactive interface, 

particularly simplifying the interpretation of linear models. 

![](https://github.com/csoneson/ExploreModelMatrix/blob/master/inst/www/ExploreModelMatrix.jpg?raw=true)

## Installation

You can install `ExploreModelMatrix` from Bioconductor (note that you need 

at least release 3.11 of Bioconductor, released in April 2020):

```

if (!requireNamespace("BiocManager", quietly = TRUE))

    install.packages("BiocManager")

BiocManager::install("ExploreModelMatrix")

```

## Usage

The main function in the `ExploreModelMatrix` package is called

`ExploreModelMatrix()`. When calling `ExploreModelMatrix()`, simply provide a

_data.frame_ (or _DataFrame_) with sample information and a design formula:

```

sampleData <- data.frame(genotype = rep(c("A", "B"), each = 4),

                         treatment = rep(c("ctrl", "trt"), 4))

ExploreModelMatrix(sampleData = sampleData,

                   designFormula = ~ genotype + treatment)

```

This will open up an [R/Shiny](https://shiny.rstudio.com/) application where you

can explore the specified design matrix and the fitted values for each

combination of predictor values.

For more examples of designs, we refer to the package vignette.