SCPline: An interactive framework for the single-cell proteomics data preprocessing.

Abstract

Single-cell proteomics has advanced our understanding of cellular complexity by enabling detailed analysis of protein expression at the single-cell level. However, challenges such as data sparsity, variability, and noise require sophisticated computational solutions. SCPline addresses these by offering a comprehensive data preprocessing and analysis platform specifically for single-cell proteomics. It supports mass spectrometry-based, antibody-based, and multi-omics approaches, performing quality screening, normalization, dimensionality reduction, and clustering for each data type (https://bioinform.nefu.edu.cn/ScPline/). Each module includes tailored functions and visualizations for easy quality checks, allowing researchers with limited programming experience to efficiently preprocess data. By streamlining complex workflows, SCPline makes advanced computational tools accessible, enabling researchers to explore cellular heterogeneity and biological states, thus accelerating discoveries in developmental biology, disease pathogenesis, and therapeutic responses. Additionally, SCPline enhances reproducibility and rigor in proteomics research, contributing to breakthroughs in understanding cellular behavior and identifying novel therapeutic targets, shaping the future of biomedical research and precision medicine.