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

By Philip A. Ewels, Måns Magnusson, Sverker Lundin, Max Käller. Bioinform., 2016

8,303 citations recorded by the source corpus.

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

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/f581ffaa6a409b36c249dd7453ccde16bb8cb89c

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Citations in the corpus

Gfastats: conversion, evaluation and manipulation of genome sequences using assembly graphs (2022, background): “eu) and as a MultiQC module [1] (https://github.”
The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update (2018, background): “Examples of new tools include: GEMINI for exploring genetic variation (12); mothur for analyzing rRNA gene sequences (13); QIIME for quantitative microbiome analysis from raw DNA sequencing data (14); deepTools for explorative analysis of deeply sequence data (15,16); HiCexplorer (17) for analysis a”
Next-Generation Sequencing Technology: Current Trends and Advancements (2023, methodology): “MethylDackel * Differential methylation Metilene [138], BSsmooth [139], methylKit [140] Epigenomics-ChIP [147], MAnorm [148], MMDiff [149]”
Falco: high-speed FastQC emulation for quality control of sequencing data (2019, positive): “Its analysis reports have become the standard for several QC tools, and automated analysis pipelines often rely on its evaluation as a safety criteria to proceed with downstream steps or, alternatively, to filter, trim or ultimately discard the data 11,12 .”
A review of methods and databases for metagenomic classification and assembly (2019, background): “FastQC) into one report [40] http://multiqc.”