The proliferation of complex proteomics experiments and the advent of plenty of new workflows often developed by and for computational biologists act as a barrier in the efficient generation of meaningful biological results, particularly for those not trained in computational methods. Mass Dynamics 2.0 (MD 2.0) exists to make current and new methodologies accessible to all researchers in an intuitive web and cloud-based collaborative environment. We introduce here the new Dataset Service in MD 2.0, engineered to easily incorporate new workflows as well as to be adopted by researchers with any computational skill level.
The Dataset Service revolutionizes data interrogation by enabling multiple dataset re-analyses and facilitating seamless workflow integration. Every iteration and detail of the data is securely stored for easy evaluation and comparison via an intuitive user interface. The most recent additions to the service are the ability to generate dose-response analyses, perform several types of normalization, imputation and dimensionality reduction techniques. This study showcases its debut version illustrating how a robust dose-response analysis can be quickly achieved in MD 2.0 (Hannah B.L.J et al 2022).
After upload and quality control, the distributions of the intensities are assessed using interactive boxplots and PCA before and after applying different combinations of normalization and imputation methods. This showcases a typical iterative approach applicable to any proteomics study to aid the decision of what pre-processing steps are more suited for the data. Subsequently, a dose-response dataset is generated and proteins responsive to the treatment are prioritized via selection on volcano plots and simultaneously visualized in dose-response curves, confirming the published results.
In summary, the Dataset Service in MD 2.0 represents a paradigm shift in proteomics data analysis. Researchers with any skill level can now explore multiple iterations on one dataset in a collaborative environment.