Bioinformatics Seminar
Time: 11AM
Venue: Davis Auditorium and Online
3 June 2025
NASpaMTP - A Tool With Approaches in Spatial Multi-omics Data Mining to Uncover the Biological Context
Tianyao LuWEHI Bioinformatics/Personalised Oncology
The spatial measurement of multi-modal data offers an unprecedented opportunity to comprehensively investigate molecular regulation at transcriptional, translational, and metabolic levels, enhancing our understanding of the cellular mechanisms underlying health and disease. Despite the growing importance of spatial metabolomics, there remains a significant gap in analytical tools capable of integrating diverse spatial omics datasets. To address this, we present SpaMTP, a versatile R-based software package that enables end-to-end integration and analysis of spatial metabolomics and transcriptomics data. SpaMTP leverages the metabolomics processing capabilities of Cardinal and integrates them with the cell-centric analytical framework of Seurat. SpaMTP features a comprehensive pipeline, including: (1) automated annotation of mass-to-charge (m/z) metabolites; (2) diverse downstream statistical analyses such as differential expression, pathway enrichment, and correlation analysis; (3) integrative spatial omics workflows; and (4) a suite of customizable visualization tools. Designed for flexibility and interoperability, SpaMTP supports various data import/export formats and enables seamless compatibility with other R and Python-based tools. We demonstrate SpaMTP's utility in uncovering novel biological insights through the analysis of two distinct biological systems. This software provides a valuable resource for the spatial multi-omics and metabolomics research community