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MultiQC: Quick start

This tutorial covers installation and first run for a typical user. It's not meant to be comprehensive - see the rest of the documentation for that - it's just to get the majority up and running quickly so you can get a taste for how to use MultiQC.

Install Conda​

In order to install MultiQC, we first need Python. Arguably, the easiest way to do this is with Conda (see full docs).

  1. Download miniconda for your operating system.
  2. Run the bash script and follow the prompts.
  3. Restart your terminal shell.
  4. Configure your conda channels to work with BioConda: 
    conda config --add channels defaults
    conda config --add channels bioconda
    conda config --add channels conda-forge
    conda config --set channel_priority strict
  5. Create a new conda environment: 
    conda create --name myenv python=3.11
    conda activate myenv

Install MultiQC​

Now that we have Python, we can install MultiQC. As we're already using Conda, we may as well install MultiQC with Conda too (see full docs).

conda install multiqc

Check that it worked by printing the MultiQC version (or --help text):

multiqc --version
multiqc, version 1.20

Get some example data​

To try MultiQC out quickly, you can fetch some example input data from the Example reports page.

Each example report has a link to Download input data. You should be able to recreate the example report using this.

For example, for the RNA-seq report:

curl -O -J -L http://multiqc.info/examples/rna-seq/data.zip
unzip data.zip

You should now have a directory called data which is full of analysis result files.

For the RNA-seq example, we have outputs from a bioinformatics analysis of some publicly available data. We have logs and reports from FastQC, TrimGalore! (Cutadapt), STAR and featureCounts.

Run MultiQC​

There isn't much to running MultiQC really - just point it at the directory that contains your files and it will search recursively for anything it recognises.

Assuming that you are still in the directory where you just extracted the data, the current working directory (.) contains your files:

multiqc .
  /// MultiQC 🔍 | v1.20

|           multiqc | Search path : /demo/data
|         searching | ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 121/121
|    feature_counts | Found 8 reports
|              star | Found 8 reports
|          cutadapt | Found 16 reports
|            fastqc | Found 32 reports
|           multiqc | Report      : multiqc_report.html
|           multiqc | Data        : multiqc_data
|           multiqc | MultiQC complete

Open the report​

You can see in the log output that MultiQC created a file called multiqc_report.html. Open it and take a look (you can usually ctrl/cmd + click the filename in most terminals). It should look basically the same as the example report on the MultiQC website.

Try using the toolbox features in the right hand sidebar, for example hiding and highlighting specific samples.

Also have a look at the directory multiqc_data that was created. This contains the parsed data in a nice friendly format, ready for any further downstream analysis.