Merge CSV outputs of PEAKS Studio

Required inputs:

• raw_dir: path to a folder containing multiple CSV files. Note that the name of each file in the folder will be used (extension excluded) as sample identifier to name the columns in the merged table.
• out_file: file name for the merged tables.

Set-up the environment:

• R needs to be installed on the computer. Please follow the instruction provided under Download and Install R at https://cran.r-project.org/

• Install the necessary packages:

  • Start an R session

  • Type in the following code and follow the prompted instructions:

    required_libs <- c("optparse","tidyverse")
    missing_libs <- required_libs[!required_libs %in% rownames(installed.packages())]
    if (length(missing_libs) > 1) {
      cat("Installing missing packages: ", paste(missing_libs, collapse = ", "), "\n\n")
      sapply(missing_libs, function(i) install.packages(i))
    }
    invisible(lapply(required_libs, library, character.only = TRUE))
    

• Fetch the tool repository

  • in Windows:

    • Almost at the top of this GitHub page, click "<> Code"
    • Click on "Download ZIP"
    • Save and extract the file where you prefer (e.g. C:\Users\Luca\Tools)

  • in Linux:

    open a terminal and type:

    sudo apt update
    sudo apt install git
    cd /home/user/tools # or to whatever folder in which you want to save the tool
    git clone https://github.com/lucaz88/PEAKS_merger.git
    

How to run:

For Windows system:

• Press the Windows Start button on the screen or keyboard
• Type in "Command Prompt"
• Left click on Command Prompt
• Move into the repository folder cd C:\Users\Luca\Tools\PEAKS_merger-main in which toy files are provided to test the tool
• Type "C:\Program Files\R\R-4.2.2\bin\Rscript.exe" PEAKS_merger_v0.1.R -r toy_data -o merged_toy_tab.csv # update the paths to where you actually installed R and downloaded the repo

For Linux system:

open a terminal and type:

cd /home/user/tools/PEAKS_merger
Rscript PEAKS_merger_v0.1.R -r toy_data -o merged_toy_tab.csv

To run you own sample simply cd into the project folder with your data and provide the related values for -r and -o arguments.