---
title: "DAPAR user manual"
author: 
- name: Samuel Wieczorek
- name: Thomas Burger
package: DAPAR
abstract: >
    The package DAPAR is a Bioconductor distributed R package which 
    provides all the necessary functions to analyze quantitative data from 
    label-free proteomics experiments. 
    Contrarily to most other similar R packages, it is endowed with rich and 
    user-friendly graphical interfaces, so that no programming skill is 
    required (see `Prostar` package).
date: "`r Sys.Date()`"
output:
    BiocStyle::html_document:
        highlight: tango
vignette: >
    %\VignetteIndexEntry{Prostar User Manual}
    %\VignetteEngine{knitr::rmarkdown}
    %%\VignetteKeywords{Mass Spectrometry, Quantitative}
    %\VignetteEncoding{UTF-8}
---

\newcommand{\shellcmd}[1]{\\\indent\indent\texttt{\footnotesize\# #1}}

\newcommand{\Rcmd}[1]{\\\indent\indent\texttt{\footnotesize\# #1}}

\newcommand{\bordurefigure}[1]{\fbox{\includegraphics{#1}}}

```{r init, echo=FALSE}
BiocStyle::markdown()
```

# Introduction

The `DAPAR` and `Prostar` packages are a series of software dedicated to 
the processing of proteomics data. More precisely, they are devoted to the 
analysis of quantitative datasets produced by bottom-up discovery proteomics 
experiments with a LC-MS/MS pipeline (Liquid Chromatography and Tandem Mass 
spectrometry).
`DAPAR` (Differential Analysis of Protein Abundance with R) is an R 
package that contains all the necessary functions to process the data in 
command lines. It can be used on its own; or as a complement to the numerous 
Bioconductor packages (\url{https://www.bioconductor.org/}) it is compliant 
with; or through the `Prostar` interface.
`Prostar` (Proteomics statistical analysis with R) is a 
web interface based on Shiny technology (\url{http://shiny.rstudio.com/}) that 
provides GUI (Graphical User Interfaces) to all the `DAPAR` functionalities, 
so as to guide any practitioner that is not comfortable with R programming 
through the complete quantitative analysis process.
The experiment package `DAPARdata` contains many datasets that can be used as 
 examples.


```{r sessioninfo}
sessionInfo()
```