Eatomics

Eatomics analyzes quantitative proteomics data from MaxQuant to provide quality control, differential abundance/expression analysis, and pathway enrichment interpretation.

Key Features:

• MaxQuant input support: Processes quantitative proteomics data generated by MaxQuant.
• Experimental design module: Translates research hypotheses into specific formulas for differential abundance and enrichment analysis.
• Quality control: Implements comprehensive quality control measures for proteomics datasets.
• Differential abundance/expression analysis: Performs statistical analyses for differential protein abundance and expression.
• Pathway enrichment analysis: Conducts pathway enrichment analyses for biological interpretation of proteomic changes.
• Interactive exploration and customization: Enables interactive data exploration and customizable analysis configurations.
• Report and visualization generation: Produces analytical reports and visualizations of processed proteomics data.
• Implementation: Built using the R Shiny framework.

Scientific Applications:

• Quantitative proteomics analysis: Analysis and interpretation of label-free or labeled quantitative proteomics datasets from MaxQuant.
• Quality assessment: Quality control and assessment of proteomics data prior to downstream analysis.
• Differential testing: Identification of differentially abundant or expressed proteins between conditions.
• Pathway-level interpretation: Functional and pathway enrichment analysis to interpret proteomic changes.
• Complex experimental designs: Analysis of complex sample layouts such as tissue biopsy studies using custom experimental design formulas.

Methodology:

Processes MaxQuant quantitative proteomics outputs; uses an experimental design module to convert hypotheses into specific formulas for differential abundance and enrichment analysis; performs quality control, differential expression/abundance, and pathway enrichment analyses; and generates reports and visualizations within an R Shiny implementation.