mlusignan / MultiQC

Aggregate results from bioinformatics analyses across many samples into a single report.

Aggregate bioinformatics results across many samples into a single report.

Find documentation and example reports at http://multiqc.info

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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).

Installation

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

MultiQC is also available in the Galaxy Toolshed.

Usage

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 & Support

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.

There is a chat room for the package hosted on Gitter where you can discuss things with the package author and other developers: https://gitter.im/ewels/MultiQC

If in doubt, feel free to get in touch with the author directly: @ewels ([e-mail])

Contributors

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