QC-espresso: Brewing quality in proteomics
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.