<div align="center"> <img src="www/logo.svg" width="200"/> <div> </div> <b>An Ensemble Bioinformatic Platform to Empower Interactive Analysis of Quantitative Phosphoproteomics.</b> <div> </div>

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📘Doc for R package 📙Doc for Web server and Local UI

<b>Table of Contents</b>

Brief Description
How to install
- 1. Docker-based installation
- 2. R-based installation
How to use
How to extend
Detail of R package "PhosMap"
Friendly suggestion
Reporting issues
Contributing
Citation

Brief Description

PhosMap emerges as an all-encompassing bioinformatic framework meticulously architected to bestow researchers with a harmonious and interactive data analysis experience within the domain of MS-based phosphoproteomics.

PhosMap is capable to handle both label-free and label-based phosphoproteomics. Moreover, PhosMap supports both the DDA- or DIA-MS phosphoproteomics data preprocessed by various types of commonly used softwares, including MaxQuant, Firmiana, Spectronaut and DIA-NN.

Serving as a versatile and user-friendly platform, PhosMap extends its prowess through a trifecta of deployment options: a web server, a local graphical interface, and an R package. For users without bioinformatics skills, the web server is suitable for analyzing small data volumes. When dealing with larger data volumes, it is recommended to utilize the local graphical interface of PhosMap. Meanwhile, for users with programming skills, the locally installed graphical interface allows for convenient customization and expansion. Moreover, the PhosMap R package offers a highly flexible platform for advanced analysis.

The PhosMap web server can be accessed at the following URL: https://huggingface.co/spaces/Bio-Add/PhosMap.

How to install

To fully unleash the potential of PhosMap, we recommend users to utilize the local version. There are two different ways to launch PhosMap:

1. Docker-based installation

We provide a docker image with PhosMap: https://hub.docker.com/r/liuzandh/phosmap

Pull the docker image of PhosMap:

docker pull liuzandh/phosmap:1.0.0

Create a docker container containing PhosMap:

docker run  -p HostPort:3838 liuzandh/phosmap:1.0.0

Then, you can enter PhosMap by visiting HostIP:HostPort.

For example: HostPort could be set to 8083. This parameter can be changed according to user needs. such as,

docker run -p 8083:3838 liuzandh/phosmap:1.0.0

Next, open 127.0.0.1:8083 in the local browser or remotely access ip:8083 (you should ensure that the machine can be accessed remotely).

2. R-based installation

This tool is developed with R, so if you want to run it locally, you may do some preparatory work:

[1] Install R. You can download R from here: https://www.r-project.org/.
[2] Install RStudio. You can download RStudio from here: https://www.rstudio.com/.
[3] Download the source code from github.
[4] Download the necessary data. <img src="www/unzip.jpg" width=18% align="right"> Please download "PhosMap_datasets.zip" from https://github.com/liuzan-info/PhosMap_datasets. Using 'git clone' is recommended. If you are not familiar with Git or experience network issues, you may download from <a href="https://pan.baidu.com/s/1o3CVRjvCIHnqfY0Bh9X-qw?pwd=7d2k" target="_blank">here</a> instead. Then unzip this file to phosmap folder like this pic.

[5] Check packages. After installing R and RStudio, you should check whether you have installed these packages ("shiny","shinyjs","shinyBS","shinyWidgets","ggplot2","ggrepel","plotly","colourpicker","ggseqlogo","pheatmap","survminer","survival","zip","stringr","readr","dplyr","DT","png","svglite","ggplotify","bslib","ksea","rmotifx","PhosMap","qpdf","pcaMethods","impute","rrcovNA","e1071","heatmaply").

You can run the codes below to install them:

if (!require("BiocManager", quietly = TRUE)){install.packages("BiocManager")}

BiocManager::install(c("pcaMethods", "impute"))

install.packages(c("FactoMineR","factoextra","data.table","tidyr","shiny","shinyjs","shinyBS","shinyWidgets","ggplot2","ggrepel","plotly", "colourpicker","ggseqlogo","pheatmap","survminer","survival","zip","stringr","dplyr","DT","png", "svglite","ggplotify","bslib","qpdf", "rrcovNA", "e1071", "heatmaply", "ggdendro))

install.packages('devtools')
require(devtools)

install_github('evocellnet/ksea')
install_github('ecnuzdd/PhosMap')

remove.packages('Matrix')
install_version('Matrix', version='1.5-3')

[6] click "Run App". View the file ui.R, then just click button "Run App", Phosmap will start.

How to use

You can find comprehensive documentation and an in-depth video tutorial on this website. https://github.com/liuzan-info/PhosMap

How to extend

Due to its clear design and reliance solely on the R language, PhosMap allows for easy customization of user-defined features. Basic knowledge of R is sufficient, without the need to understand the shiny framework. We provide a step-by-step tutorial available here.

Follow the instructions in How to install --> R-based installation for installation. Additionally, install the packages required for your customized functionalities.

Open the ui.R file inside the PhosMap folder and search for the term 'Customization.' You will then see a template with detailed annotations. You only need to selectively modify the lines with annotations according to the instructions. These codes determine the display of the graphical interface.

# If you want to expand the software's functionality, 
# please uncomment the code below. 
# Tip: You can use the Ctrl+Shift+C shortcut to uncomment or comment the selectedcode.
tabPanel(
  "Customization",
  h2("User-defined Tool", class = "tooltitle"),
  h4("This module is designed for implementing user-defined functionalities. 
     If you have any questions, please submit an issue on Github.", class = "toolsubtitle"),
  fluidRow(
    column(
      4,
      panel(
        "",
        heading = "Parameters Setting",
        numericInput(
          inputId = "user_num1",  # id to be used in server.R, must be unique, is not recommended to change.
          label = "user_num1",  # label to show that can be changed.
          value = 1,  # default number that can be changed.
        ),
        numericInput(
          inputId = "user_num2",  # id to be used in server.R, must be unique, is not recommended to change.
          label = "user_num2",  # label to show that can be changed.
          value = 1,  # default number that can be changed.
        ),
        actionButton(
          inputId = "user_button",  # id to be used in server.R, must be unique, is not recommended to change.
          label = "Run", # label to show that can be changed.
        )
      )
    ),
    column(
      8,
      h4("Result--Table:"),  # instruction, not recommended to change.
      dataTableOutput(
        outputId = "user_table",  # id to be used in server.R, must be unique, is not recommended to change.
      ),
      h4("Result--Plot:"),  # instruction, not recommended to change.
      plotOutput(
        outputId = "user_plot",  # id to be used in server.R, must be unique, is not recommended to change.
      )
    )
  )
)

Open the server.R file inside the PhosMap folder and search for the term 'Customization.' You will then see a template with detailed annotations. We demonstrate the data retrieval and utilization, along with the computational core code that you can modify as desired, and how to ultimately display data frames and images in the UI interface. These codes determine how the calculations are performed.
```
# If you want to expand the software's functionality, 
# please uncomment the code below. 
# Tip: You can use the Ctrl+Shift+C sh
```

PhosMap

Install / Use

README