# _MatrixQCvis_ - Interactive exploration of data quality
## Overview
The _MatrixQCvis_ package provides shiny-based interactive visualization of
data quality metrics at the per-sample and per-feature level. It is broadly
applicable to quantitative omics data types that come in matrix-like format
(features x samples). It enables the detection of low-quality samples, drifts,
outliers and batch effects in data sets. Visualizations include amongst
others bar- and violin plots of the (count/intensity) values, mean vs standard
deviation plots, MA plots, empirical cumulative distribution function (ECDF)
plots, visualizations of the distances between samples, and multiple types of
dimension reduction plots.
Furthermore, _MatrixQCvis_ allows for differential expression analysis based
on the _limma_ (moderated t-tests) and _proDA_ (Wald tests) packages.
_MatrixQCvis_ builds upon the popular Bioconductor _SummarizedExperiment_
S4 class and enables thus the facile integration into existing workflows.
The package is especially tailored towards metabolomics and proteomics mass
spectrometry data, but also allows to assess the data quality of other data
types that can be represented in a _SummarizedExperiment_ object.
## Installation
To install _MatrixQCvis_ from GitHub, install the package via `devtools`:
```r
if (!requireNamespace("devtools", quietly = TRUE))
install.packages("devtools")
library(devtools)
install_github("tnaake/MatrixQCvis")
```
Alternatively, the _MatrixQCvis_ package can also be installed via the
Bioconductor project.
For the [release](http://bioconductor.org/packages/release/bioc/html/MatrixQCvis.html)
version enter:
```r
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("MatrixQCvis")
```
For the [development](http://bioconductor.org/packages/devel/bioc/html/MatrixQCvis.html)
version enter:
```r
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# the following initializes usage of Bioc devel
BiocManager::install(version = "devel")
BiocManager::install("MatrixQCvis")
```
The version at the Bioconductor development branch and the code in the Github repository
are places where we publicly disclose our development process and users are
supposed to refer to the Bioconductor releae version as the authoritative version for
use.
## Quick start
_MatrixQCvis_ is based on the _SummarizedExperiment_ class. The shiny
application can be started with passing a _SummarizedExperiment_ object
(in the following denoted as _se_) or without such an object. The
second function call will load an interface to load a
_SummarizedExperiment_ object stored in a RDS file.
```r
library("MatrixQCvis")
## initialize the application with passing a SummarizedExperiment object
shinyQC(se)
## initialize the application without passing a SummarizedExperiment object
shinyQC()
```
