ProteoIntegrator: Harmonized Multi-Source Proteomics Data for Differential Analysis

ProteoIntegrator is a scalable platform for harmonizing and analyzing multi-source proteomics data, benchmarked on DDA/DIA and multi-instrument datasets. The tool automates quality control, differential expression analysis, and pathway enrichment, and was used to reanalyze published kidney cancer datasets. Yan Ren uploaded this dataset to figshare on 2026-05-23.

Use Cases

• Correcting batch effects and instrument drift across datasets based on the integrated ComBat method.
• Imputing missing values in proteomics data based on the benchmarked Bayesian principal component analysis (BPCA).
• Identifying differentially expressed proteins (DEPs) based on automated differential expression analysis.
• Conducting pathway enrichment and protein-protein interaction network analysis based on integrated functional modules.
• Harmonizing public proteomics datasets from varied platforms and gradients based on the described cross-laboratory analyses.

Strengths

• Benchmarked 12 imputation methods on DDA/DIA and multi-instrument datasets.
• Demonstrated >98% quantification accuracy when integrating DDA/DIA/TMT data.
• Batch correction capable of handling >1000 samples in under 1 minute.
• Utility demonstrated by recapitulating metabolic shifts in reanalyzed kidney cancer datasets.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is relatively small at 2.0 MB, suggesting it may contain processed results or code rather than raw proteomics data.

Provenance

Source

Yan Ren via figshare.

Collection Method

Likely contains processed proteomics data, benchmark results, and analysis outputs from the ProteoIntegrator platform.

Freshness

Last updated 2026-05-23 13:05:30; freshness should be verified.