MultiQC is a tool to create a single report with interactive plots for multiple bioinformatics analyses across many samples.

MultiQC is written in Python (tested with v2.7 / v3.4 / v3.5). It is available on the Python Package Index and through conda using Bioconda.

Reports are generated by scanning given directories for recognised log files. These are parsed and a single HTML report is generated summarising the statistics for all logs found. MultiQC reports can describe multiple analysis steps and large numbers of samples within a single plot, and multiple analysis tools making it ideal for routine fast quality control.

Currently, supported tools include:

• Quality control & pre-processing
  • FastQC
  • FastQ Screen
  • Cutadapt
  • Trimmomatic
  • Skewer
• Read aligners / quantifiers
  • Salmon
  • Kallisto
  • STAR
  • Tophat
  • Bowtie
  • Bowtie 2
  • Bismark
  • HiCUP
• Post-alignment tools
  • RSeQC (bam_stat, gene_body_coverage, inner_distance, junction_annotation, junction_saturation, read_distribution, read_duplication, read_gc)
  • Subread featureCounts
  • Samblaster
  • Bamtools (stats)
  • Samtools stats
  • Picard (MarkDuplicates, InsertSizeMetrics, GcBiasMetrics, HsMetrics, OxoGMetrics)
  • Preseq
  • methylQA
  • Qualimap (BamQC, RNASeq)
  • SnpEff

More modules are being written all of the time. Please suggest any ideas as a new issue (include an example log file if possible).

You can install MultiQC from PyPI using pip as follows:

pip install multiqc

If you would like the development version instead, the command is:

pip install git+https://github.com/ewels/MultiQC.git

Alternatively, you can install using Conda from the bioconda channel:

conda install -c bioconda multiqc

Once installed, you can use MultiQC by navigating to your analysis directory (or a parent directory) and running the tool:

multiqc .

That's it! MultiQC will scan the specified directory ('.' is the current dir) and produce a report detailing whatever it finds.

The report is created in multiqc_report.html by default. Tab-delimited data files are also created in multiqc_data/, containing extra information. These can be easily inspected using Excel (use --data-format to get yaml or json instead).

For more detailed instructions, run multiqc -h or see the documentation.

Contributions and suggestions for new features are welcome, as are bug reports! Please create a new issue for any of these, including example reports where possible. MultiQC has extensive documentation describing how to write new modules, plugins and templates.

If in doubt, feel free to get in touch with the author: @ewels (phil.ewels@scilifelab.se)

Many thanks to those who have helped out with with project so far:

• Project lead and main author: @ewels
• Early code refactoring help: @moonso
• Early version of Qualimap module: @guillermo-carrasco
• Skewer and Samblaster modules: @dakl
• Samtools stats module: @lpantano
• Tweaks / core help: @robinandeer and @avilella