Sign in
BioinformaticsbioRxiv
Preprint

CAT-APP: Contamination Analysis and Tempering--An Automated Online Platform for Plasma Proteomics with Data Rescuing Capabilities

Mingming NiuiD, Dong ZhangiD, Zhiwei ZhouiD, Jiaqi ZhangiD, Rong ZhangiD, Long SheniD, Hong WangiD

Abstract

Plasma and serum proteome profiling have become central to biomarker discovery for medical research. The advent of high-throughput plasma proteomics pipelines has enabled the generation of massive datasets. However, biomarker discovery is frequently compromised by sample contamination, primarily from erythrocytes, platelets, and coagulation factors. Such contamination can lead to the false identification of contaminants as biomarkers in over 50% of studies or obscure genuine biomarkers due to contamination-induced variability. Currently, no tools are available to salvage such compromised data, and the default approach is often to discard the affected samples. To address this gap, we introduce CAT-APP (Contamination Analysis and Tempering-An Automated Online Platform for Plasma Proteomics). CAT-APP tackles contamination through three key modules: multi-dimensional contamination assessment and adaptive contamination indexing, mathematical model-based contamination tempering, and data recovery evaluation with visualization. We applied CAT-APP to 28 independent plasma proteomics datasets and found that 82% exhibited contamination issues. CAT-APP markedly improved data quality by removing false-positive biomarkers introduced by contamination and restoring true biological signals that were previously obscured in representative datasets. To promote widespread adoption, we provide CAT-APP as an freely accessible, user-friendly, and robust web platform at https://www.bloodecosystem.com/tools/CAT-APP/.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.