The Galaxy bioinformatics framework is used by thousands of cancer researchers, primarily for genomics-based studies. It's open and flexible environment enables interoperation of diverse bioinformatics software via a user-friendly web-based interface. Despite its proven value for genomic bioinformatics, Galaxy's potential for enabling cancer research has not been fully realized. One area of emerging potential for Galaxy is multi- omic informatics. Multi-omics integrates high throughput genomic, transcriptomic, proteomic and metabolomics data to reveal new molecular discoveries in cancer. For example, integrating metabolomics information with genomic and/or proteomic data reveals biochemical consequences of gene and protein variations underlying carcinogenesis. Integration of genomic or transcriptomic data with mass spectrometry (MS)-based proteomic data (proteogenomics) identifies novel protein variants linked to genome mutations. Integration of metagenomic data with MS-based proteomic data (metaproteomics) identifies proteins expressed by microbial communities giving insights into biochemical contributions from the microbiome to carcinogenesis. Despite their potential pay-off, these multi-omic approaches require use of diverse informatics tools out of the reach of most bench researchers. Fortunately, Galaxy offers a solution. We propose to extend Galaxy and create a powerful, unified hub for multi-omic informatics. We will focus on enhancing Galaxy with a stand-alone Multi-omics Visualization Platform (MVP) for results visualization and interpretation. We will build novel Galaxy extensions enabling metabolite profiling, results interpretation and targeted clinical validation studies. We will extend current Galaxy-based tools to create a complete solution for proteogenomic and metaproteomic informatics, making easy-to-build workflows that ensure accurate results. Finally, we will empower cancer researchers to use Galaxy for multi-omics in their work via a variety of dissemination and training activities. We will achieve these outcomes via these Specific Aims: 1) Extend a Galaxy-compatible Multi-omics Visualization Platform (MVP) for enhanced results interpretation and data exchange utilizing cancer knowledge bases and informatics resources; 2) Extend Galaxy and the MVP tool for metabolite profiling in cancer research; 3) Extend Galaxy and the MVP tool for integrative genomic-proteomic informatics and workflows.; 4) Catalyze the use of multi-omic workflows and associated tools by cancer researchers via dissemination, promotion and training activities. Our work will be guided via driving cancer projects with a network of collaborators. We will partner with developers of established software and methods in different 'omic domains, and utilize world-class infrastructure at the Minnesota Supercomputing Institute. Our deliverables will directly complement other projects currently funded through the NIH ITCR program. The upshot of our work will be a large network of cancer researchers empowered to utilize high impact, multi-omic approaches, ultimately catalyzing new discoveries that will help decrease the suffering and death from cancer.
The proposed work seeks to extend the Galaxy bioinformatics software to create a unified, publically available resource enabling integrated analysis of data that will reveal molecular connections between genes, proteins and metabolites in cancer-relevant samples. Results from these analyses will provide new information into the molecular mechanisms of cancer, leading to better diagnosis and treatment.
| Millikin, Robert J; Solntsev, Stefan K; Shortreed, Michael R et al. (2018) Ultrafast Peptide Label-Free Quantification with FlashLFQ. J Proteome Res 17:386-391 |
| Rolfs, Zach; Solntsev, Stefan K; Shortreed, Michael R et al. (2018) Global Identification of Post-Translationally Spliced Peptides with Neo-Fusion. J Proteome Res : |
| Blank, Clemens; Easterly, Caleb; Gruening, Bjoern et al. (2018) Disseminating Metaproteomic Informatics Capabilities and Knowledge Using the Galaxy-P Framework. Proteomes 6: |
| Afiuni-Zadeh, Somaieh; Boylan, Kristin L M; Jagtap, Pratik D et al. (2018) Evaluating the potential of residual Pap test fluid as a resource for the metaproteomic analysis of the cervical-vaginal microbiome. Sci Rep 8:10868 |
| Muth, Thilo; Kohrs, Fabian; Heyer, Robert et al. (2018) MPA Portable: A Stand-Alone Software Package for Analyzing Metaproteome Samples on the Go. Anal Chem 90:685-689 |
| Jagtap, Pratik D; Viken, Kevin J; Johnson, James et al. (2018) BAL Fluid Metaproteome in Acute Respiratory Failure. Am J Respir Cell Mol Biol 59:648-652 |
| Chambers, Matthew C; Jagtap, Pratik D; Johnson, James E et al. (2017) An Accessible Proteogenomics Informatics Resource for Cancer Researchers. Cancer Res 77:e43-e46 |
