ShinyOmics

ShinyOmics facilitates collaborative exploration and comparative analysis of large-scale Tn-Seq, RNA-Seq, microarray, and proteomics datasets to interpret transcriptional and proteomic responses and to overlay those responses on metabolic networks.

Key Features:

• Multi-omics support: Processes and compares datasets from Tn-Seq, RNA-Seq, microarray, and proteomics experiments.
• Metadata integration: Accepts and integrates user-supplied metadata to associate experimental conditions with omics measurements.
• Visualization and comparison: Provides visualization options for comparing datasets, highlighting differences across omics profiles, and overlaying transcriptional responses on metabolic networks.
• Data management and sharing: Manages large-scale omics datasets and supports dataset sharing among collaborators.
• Pre-loaded datasets: Includes pre-loaded RNA-Seq and Tn-Seq datasets from Streptococcus pneumoniae and Mycobacterium tuberculosis.

Scientific Applications:

• Identification of stress-responsive proteins: Identification of protease and chaperone proteins upregulated under aminoglycoside stress in Streptococcus pneumoniae.
• Comparative antibiotic response analysis: Comparison of transcriptomic responses triggered by antibiotics with similar mechanisms of action.
• Integration with metabolic networks: Overlaying transcriptional responses on metabolic networks to interpret impacts on cellular metabolism.
• Cross-omics regulatory inference: Highlighting dissimilarities between omics profiles to inform studies of complex regulatory networks.

Methodology:

Uses datasets from Tn-Seq, RNA-Seq, microarray, and proteomics; includes pre-loaded RNA-Seq and Tn-Seq data from studies on Streptococcus pneumoniae and Mycobacterium tuberculosis, including RNA-Seq and Tn-seq data from Zhu et al., 2019 (under review) comparing strains 19F and T4 across five different antibiotics under stress conditions.