Cited by 10,143Genomics and Phylogenetic StudiesScientific Computing and Data ManagementSingle-cell and spatial transcriptomics

MultiQC: summarize analysis results for multiple tools and samples in a single report

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Ewels, Philip, Magnusson, Måns, Lundin, Sverker, Käller, Max·2016·Bioinformatics

Abstract

Motivation: Fast and accurate quality control is essential for studies involving next-generation sequencing data. Whilst numerous tools exist to quantify QC metrics, there is no common approach to flexibly integrate these across tools and large sample sets. Assessing analysis results across an entire project can be time consuming and error prone; batch effects and outlier samples can easily be missed in the early stages of analysis. Results: We present MultiQC, a tool to create a single report visualising output from multiple tools across many samples, enabling global trends and biases to be quickly identified. MultiQC can plot data from many common bioinformatics tools and is built to allow easy extension and customization. Availability and implementation: MultiQC is available with an GNU GPLv3 license on GitHub, the Python Package Index and Bioconda. Documentation and example reports are available at http://multiqc.info Contact: phil.ewels@scilifelab.se

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  1. Meyer C.A. Liu X.S. (2014) Identifying and mitigating bias in next-generation sequencing methods for chromatin biology. Nat. Rev. Genet., 15, 709721. PMC4473780 25223782
  2. Okonechnikov K. (2015) Qualimap 2: advanced multi-sample quality control for high-throughput sequencing data. Bioinformatics, 32, 292– 294. 26428292 PMC4708105
  3. Taub M.A. (2010) Overcoming bias and systematic errors in next generation sequencing data. Genome Med., 2, 87. 21144010 PMC3025429
  4. Wang L. (2012) RSeQC: quality control of RNA-seq experiments. Bioinformatics, 28, 21845. 22743226

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Authors
Ewels, P., Magnusson, M., Lundin, S., & Käller, M.
Affiliations
  • Stockholm University (SE)
  • Science for Life Laboratory (SE)
Corresponding author
Ewels, Philip
Venue
Bioinformatics
Published
2016-06-16
Volume
32
Issue
19
Pages
3047-3048
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
OpenAlex
W2432815617
Cited by
10,143
References
2
Citations by year
2026: 2080 · 2025: 2138 · 2024: 1814 · 2023: 1216 · 2022: 1089 · 2021: 840 · 2020: 481 · 2019: 302 · 2018: 130 · 2017: 42 · 2016: 7
FWCI
83.65
Type
journal article
Language
en
Open access
Locations
  • Bioinformatics (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • HighWire Press Open Archive (submittedVersion)
Funders
Science for Life Laboratory
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords
MultiQC, batch effects, outlier detection, Python
MeSH terms
Quality Control, Software, Computational Biology, High-Throughput Nucleotide Sequencing

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