综合性多组学硅肺病数据平台SilicosisOmics的构建OA

Objective To address the challenges of fragmented multi-omics data and insufficient integrated analysis in silicosis research,we aim to construct a comprehensive data platform that supports systematic analysis of multi-level molecular alterations in fibrotic lung tissues and facilitates rapid identification of therapeutic targets.Methods We systematically integrated transcriptomic,single-cell transcriptomic,quantitative proteomic,post-translational modification-specific proteomic,and metabolomic data from human and mouse silicotic and control lung tissues.By leveraging bioinformatics tools including DESeq2,Seurat,and CellChat,we developed a web-based visualization platform enabling data visualization and interactive analysis.Results We successfully constructed SilicosisOmics(https://respir.pumc.edu.cn/SilicosisOmics/),a comprehensive multi-omics data platform for silicosis research.The platform integrated five types of omics data derived from both silicotic and non-diseased lung tissues across human and mouse species.SilicosisOmics provided not only online search functionality for static visualiza-tion of gene expression and single-cell clustering but also interactive analytical tools supporting user-customized analyses including differential gene expression,pathway enrichment,and cell-cell interaction studies.Conclusions The SilicosisOmics platform offers systematic multi-omics data resources and user-friendly analytical tools for silicosis and pulmonary fibrosis research,thereby facilitating the advancement of mechanistic studies,target discovery,and subsequent translational research.