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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411
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        About MultiQC

        This report was generated using MultiQC, version 1.33

        Video: Using MultiQC Reports MultiQC homepage MultiQC documentation Source code Issue tracker

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        MultiQC is developed by Seqera.

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        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2025-12-25, 13:01 UTC based on data in: /home/runner/work/pmultiqc/pmultiqc/data_temp

        pmultiqc

        pmultiqc is a MultiQC module to show the pipeline performance of mass spectrometry based quantification pipelines such as nf-core/quantms, MaxQuant, and DIA-NN.https://github.com/bigbio/pmultiqc

        Results Overview

        Summary Table

        This table shows the summary statistics of the submitted data.
        This table shows the summary statistics of the submitted data.
        Showing 1/1 rows and 4/4 columns.
        #MS2 Spectra#Identified MS2 Spectra%Identified MS2 Spectra#Peptides Identified#Proteins Identified
        128230
        20518
        16.00%
        1523
        185

        HeatMap

        This heatmap provides an overview of the performance of quantms.
        This plot shows the pipeline performance overview.
        Created with MultiQC

        Pipeline Result Statistics

        This plot shows the submitted results
        This plot shows the submitted results. Including the number of identified peptides and the number of identified modified peptides in the submitted results. You can also remove the decoy with the `remove_decoy` parameter.
        Showing 3/3 rows and 4/4 columns.
        Spectra File#Peptide IDs#Unambiguous Peptide IDs#Modified Peptide IDs#Protein (group) IDs
        F001234
        1788
        1788
        706
        146
        F001235
        1351
        1351
        627
        130
        F001236
        1034
        1034
        543
        99

        Identification Summary

        Number of Peptides identified Per Protein

        This plot shows the number of peptides per protein in the submitted data
        Proteins supported by more peptide identifications can constitute more confident results.
        Created with MultiQC

        MS2 and Spectral Stats

        Number of Peaks per MS/MS spectrum

        Histogram of number of peaks per MS/MS spectrum.
        Too few peaks may indicate poor fragmentation; many peaks could indicate noisy spectra.
        Created with MultiQC

        Peak Intensity Distribution

        Histogram of ion intensity vs. frequency for all MS2 spectra.
        High number of low intensity noise peaks expected; disproportionate high signal peaks may indicate issues.
        Created with MultiQC

        Distribution of Precursor Charges

        Bar chart of precursor ion charge distribution.
        Use to identify potential ionization problems or unexpected distributions.
        Created with MultiQC

        MS/MS Counts Per 3D-peak

        An oversampled 3D-peak is defined as a peak whose peptide ion (same sequence and same charge state) was identified by at least two distinct MS2 spectra in the same Raw file.
        For high complexity samples, oversampling of individual 3D-peaks automatically leads to undersampling or even omission of other 3D-peaks, reducing the number of identified peptides. Oversampling occurs in low-complexity samples or long LC gradients, as well as undersized dynamic exclusion windows for data independent acquisitions.
        Created with MultiQC

        MultiQC v1.33 - Written by Phil Ewels, available on GitHub.

        This report uses Plotly, jQuery, jQuery UI, Bootstrap and FileSaver.js.