{
  "abstract": "Data-independent acquisition (DIA) proteomics has become a standard approach for high-throughput proteomics, with DIA-NN emerging as one of the most widely adopted data-analysis platforms. However, despite the detailed information available in DIA-NN output reports, proteomics researchers may lack a streamlined and reproducible approach for assessing acquisition quality, identification consistency, and quantitative reliability across experiments. QC-espresso addresses this need through an automated, report-centered quality-control workflow implemented in R and Quarto. The tool processes a DIA-NN report.parquet file together with the corresponding FASTA database and generates a structured HTML report containing plots, run-level statistics, and exportable summary tables. Application to three experimental datasets allowed the visualization of lower identification depth related to high contaminant content; a chromatographic transition accompanied by altered retention-time and peak-width behavior; and the co-occurrence of systematic mass-error bias with changes in precursor- and protein-level quantitative-quality metrics. QC-espresso can be executed directly in R or through a portable Windows distribution with a graphical launcher, with both modes using the same analytical modules and report-generation workflow. The resulting report provides a consistent record for local inspection and troubleshooting of quality-control metrics within individual DIA proteomics experiments. QC-espresso is freely available at https://github.com/lanfredig/QC-espresso_DIA.",
  "abstract_shown": true,
  "affiliations": [
    "CNPEM - Brazilian Biosciences National Laboratory"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "G. Pauperio Lanfredi"
    },
    {
      "name": "J. G. Miyamoto"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1vmatpt0x0j4n.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.29.762921",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.29.762921v1.full",
  "id": "1vmatpt0x0j4n",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.29.762921v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "biochemistry"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.29.762921v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-29",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/1vmatpt0x0j4n.ris",
  "sources": [
    {
      "first_seen": "2026-11-03T12:21:00Z",
      "native_id": "10.64898/2026.10.29.762921",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.29.762921v1"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "biorxiv:biochemistry",
      "subfield": "general"
    }
  ],
  "title": "QC-espresso: Brewing quality in proteomics",
  "title_text": "QC-espresso: Brewing quality in proteomics",
  "type": "preprint",
  "updated_at": "2026-11-04T00:21:16Z",
  "url": "https://research.draconitic.com/paper/1vmatpt0x0j4n",
  "venue": "bioRxiv",
  "versions": []
}