QC-espresso: Brewing quality in proteomics
- 1CNPEM - Brazilian Biosciences National Laboratory
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.
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BibTeX
@misc{lanfredi2026qcespresso,
title = {{QC-espresso: Brewing quality in proteomics}},
author = {G. Pauperio Lanfredi and J. G. Miyamoto},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.29.762921},
url = {https://www.biorxiv.org/content/10.64898/2026.10.29.762921v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - QC-espresso: Brewing quality in proteomics
AU - G. Pauperio Lanfredi
AU - J. G. Miyamoto
PY - 2026
DA - 2026/10/29
PB - bioRxiv
DO - 10.64898/2026.10.29.762921
UR - https://www.biorxiv.org/content/10.64898/2026.10.29.762921v1
AB - 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.
ER -