LC-MS/MS raw file data processing results by CHIonStar

Achieving deep and high-quality protein quantification is critical for LC–MS-based proteomics in pharmaceutical and clinical research. CHIonStar is a quantitative strategy that integrates ultra-high-resolution MS1-based quantification with chimeric spectrum deconvolution through rigorous feature–identification matching. This approach enables accurate and selective MS1-based quantification of individual co-eluted peptides with closely spaced precursor m/z values. In this project, CHIonStar was applied to a benchmark LC–MS/MS dataset consisting of technical replicates to evaluate quantitative accuracy and reproducibility. The benchmark samples contained human colon carcinoma (SW620) cell digests as a constant background (true negatives), spiked with varying low amounts of E. coli protein digests as true-positive proteins. Yeast digests were added to normalize the total peptide mass across samples. The dataset includes five groups (A–E), with theoretical abundance ratios of E. coli proteins in groups B, C, D, and E relative to group A of 1.5, 2, 3, and 4, respectively. The .sdb files contain quantitative information, while the .pdResult files contain identification results generated by CHIMERYS in Proteome Discoverer. For ease of uploading, the original .pdResult file was split into multiple segments. After downloading all segmented .pdResult files, please use the following command in the Terminal (macOS/Linux) to merge them into a single file: cat Tech25_CHIMERYS.pdResult.part_* > Tech25_CHIMERYS.pdResult Please use the following command in the CMD (Windows): copy /b Tech25_CHIMERYS.pdResult.part_* Tech25_CHIMERYS.pdResult