MultiQC
Open-source tool to aggregate bioinformatic analyses results.
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Built-in support for 150+ tools, enabling you to search results and compile a single report across all samples and analyses.
See all the supported tools- pip
- conda
- docker
MultiQC is the standard in bioinformatics reporting
Taught in genomic courses globally, MultiQC has become a fixture at the end of most biological data analysis pipelines. Bioinformaticians and data scientists choose MultiQC because it “just works”
- Simplify QC analysis with user-friendly HTML reports and convenient data exports
- Plot outputs from most popular bioinformatics tools, or bring your own with "custom content"
- Enable collaboration and boost research productivity by easily sharing QC data
- Detect outliers, anomalies, and batch effects with built-in visualizations
- See all samples at once, enabling comparisons without looking at individual reports
- See all tools at once, tracking your data through the analysis process
Try MultiQC in your browser
This MultiQC runner uses WebAssembly to process your data entirely in your browser. No data leaves your computer for the analysis. Note that this feature is experimental and requires a modern browser with WebAssembly support.
Sample reports
MultiQC collects numerical stats from each module at the top the report, so that you can track how your data behaves as it proceeds through your analysis.
Bisulfite Seq
MultiQC report from an analysis of DNA methylation using bisulfite sequencing.
The example methylation report is based on analysis of data from the GEO NCBI project GSE47966, from the 2013 Lister et. al. paper Global epigenomic reconfiguration during mammalian brain development.
Raw data was run through FastQC and trimmed using Trim Galore! (a wrapper around Cutadapt). Reads were aligned, deduplicated and cytosine methylation statuses called using Bismark.
You can download this report and / or the logs used to generate it, to try running MultiQC yourself:
Features
No setup required
MultiQC works out of the box, with no setup or configuration required. Data is gathered into a single interactive report, automatically extracting sample names from reports and log files for downstream analysis.
Easily scan key statistics across samples without switching files or accessing multiple QC tools.Interactive browser-based analysis
More than just a reporting tool, MultiQC provides rich visualizations, enabling analysts to explore results from multiple QC tools interactively.
Use the intuitive MultiQC interface to visualize data, sort, filter, and customize results, export visualizations to third-party tools, and visualize samples side by side.Support for 150+ tools
MultiQC automatically recognizes outputs from the most commonly used bioinformatics tools, including FastQC, Samtools, Picard, GATK, RSeQC, SnpEff, DRAGEN and many more, enabling easy analysis in a single place.
Better yet, with a vibrant, engaged open-source community and extensive documentation, the list of supported tools continues to grow, providing support for the latest tools and file formats.Built for the Seqera Platform
Built with open science in mind, MultiQC integrates seamlessly with the Seqera Platform enabling analysts in shared workspaces to easily access interactive MultiQC reports directly from the Seqera UI.
MultiQC can be used in a variety of ways and is ideally suited to being embedded as a final analysis step in analysis pipelines written in Nextflow or other workflow languages.Ready for downstream analysis
Every bioinformatics tool generates output in its own format. MultiQC standardises these, exporting data as TSV / YAML / JSON in a directory alongside the HTML report.
Easily import data generated by MultiQC for downstream analysis, for example working with single-cell filtering based on QC metrics, or creating custom analysis reports with aggregate data.Install from the Python Package Index or Bioconda.
To install MultiQC, simply run pip install multiqc on the command line.
If you use conda, run conda install multiqc instead.