ProteomProfile

ProteomProfile is a software platform for the analysis and profiling of proteomics data. It provides a workflow to quantify protein abundance across multiple samples and conditions, enabling researchers to build proteomic profiles that support biomarker discovery, comparative proteomics, and systems-level interpretation of complex datasets.

The platform accepts data from common mass spectrometry outputs and proteomics data standards, including mzML, mzXML, and peptide-to-protein mapping results. It implements normalization approaches such as total ion current, median normalization, and quantile normalization, as well as methods to correct for batch effects and technical variation.

ProteomProfile offers multiple quantification strategies, including label-free intensity-based methods and labeling-based approaches like TMT and iTRAQ. It includes differential expression analyses (for example, LIMMA, t-tests, or non-parametric tests), clustering, and dimensionality reduction (PCA, t-SNE). Functional interpretation features integrate with pathway databases (GO, KEGG, Reactome) for enrichment analysis.

The data model organizes information into proteins, peptides, samples, experiments, and associated metadata, with provenance tracking to support reproducibility. The workflow comprises data import, quality control, preprocessing, statistical analysis, visualization, and reporting. Output formats include interactive plots, summary statistics, and exportable tables suitable for downstream analyses and integration with other omics datasets.

ProteomProfile is designed for researchers in proteomics laboratories seeking an integrated tool for end-to-end analysis. It is distributed with documentation and tutorials, and supports both local installations and server deployments. By providing a transparent, auditable workflow, ProteomProfile aims to facilitate rigorous comparative studies and reproducible research in proteomics.