The article "Majorbio Cloud 2024: Update Single-Cell and Multi-Omics Workflows" by Chang Han et al. discusses the advancements in high-throughput multiomics technologies and their impact on life science and medical research. The authors highlight the importance of bioinformatics tools and pipelines for analyzing complex multiomics data, which is increasingly required due to the growing volume of data. Majorbio Cloud (https://cloud.majorbio.com/) is introduced as a user-friendly platform that supports the analysis of various omics data, including transcriptome, proteome, metabolome, and metagenome. The article details three key workflows: 1. **Single-Cell Transcriptomics Workflow**: This workflow includes six steps: data preprocessing, cell filtration, batch effect removal, clustering, marker gene identification, and downstream analysis. It uses tools like Cell Ranger and Seurat for data processing and analysis. 2. **Proteomics Workflow**: This workflow consists of seven main modules: data processing, protein expression and functional annotation, statistical analysis, protein set analysis, weighted gene correlation network analysis (WGCNA), gene set enrichment analysis (GSEA), and time-series data analysis. It supports label-free quantitation and label-based quantitative proteomics. 3. **Metabolomics Workflow**: This workflow includes five steps: data preprocessing, sample comparison analysis, metabolite annotation, differential expression metabolites analysis, and metabolite set analysis. It uses methods like PCA and PLS-DA for statistical analysis. The article also introduces an integrated multiomics pipeline that combines transcriptomic and proteomic data for differential expression analysis, correlation analysis, functional annotation, and interactive visualization. Additionally, it describes a new interactive analysis mode called "Pipeline + Extensions," which allows users to perform more in-depth data mining using extension tools. Since its launch in 2016, Majorbio Cloud has been used by over 150,000 users from more than 9,000 institutions, completing over 600,000 omics data mining tasks. The platform has been cited in numerous journal articles, and the authors plan to continuously update and improve the platform to enhance user experience and analytical capabilities.The article "Majorbio Cloud 2024: Update Single-Cell and Multi-Omics Workflows" by Chang Han et al. discusses the advancements in high-throughput multiomics technologies and their impact on life science and medical research. The authors highlight the importance of bioinformatics tools and pipelines for analyzing complex multiomics data, which is increasingly required due to the growing volume of data. Majorbio Cloud (https://cloud.majorbio.com/) is introduced as a user-friendly platform that supports the analysis of various omics data, including transcriptome, proteome, metabolome, and metagenome. The article details three key workflows: 1. **Single-Cell Transcriptomics Workflow**: This workflow includes six steps: data preprocessing, cell filtration, batch effect removal, clustering, marker gene identification, and downstream analysis. It uses tools like Cell Ranger and Seurat for data processing and analysis. 2. **Proteomics Workflow**: This workflow consists of seven main modules: data processing, protein expression and functional annotation, statistical analysis, protein set analysis, weighted gene correlation network analysis (WGCNA), gene set enrichment analysis (GSEA), and time-series data analysis. It supports label-free quantitation and label-based quantitative proteomics. 3. **Metabolomics Workflow**: This workflow includes five steps: data preprocessing, sample comparison analysis, metabolite annotation, differential expression metabolites analysis, and metabolite set analysis. It uses methods like PCA and PLS-DA for statistical analysis. The article also introduces an integrated multiomics pipeline that combines transcriptomic and proteomic data for differential expression analysis, correlation analysis, functional annotation, and interactive visualization. Additionally, it describes a new interactive analysis mode called "Pipeline + Extensions," which allows users to perform more in-depth data mining using extension tools. Since its launch in 2016, Majorbio Cloud has been used by over 150,000 users from more than 9,000 institutions, completing over 600,000 omics data mining tasks. The platform has been cited in numerous journal articles, and the authors plan to continuously update and improve the platform to enhance user experience and analytical capabilities.