Genoppi

Genoppi integrates quantitative proteomic data with genetic datasets to provide a standardized statistical framework for combined analyses of proteomic and genetic information.

Key Features:

• Quality Control: Systematic quality control measures validate proteomic data prior to integration.
• Data Integration: Integration of quantitative proteomic results with genetic datasets enables joint analysis of protein interactions and genetic signals.
• External Dataset Compatibility: Incorporates external resources such as published protein-protein interactions, gene set annotations, and user-defined inputs.

Scientific Applications:

• Hypothesis generation: Generates biological insights and therapeutic hypotheses from combined proteomic and genetic analyses.
• Cell-type-specific interaction analysis: Enables analysis of cell-type-specific protein interaction datasets, demonstrated on sixteen datasets for proteins involved in cancer and neurological diseases such as TDP-43, MDM2, PTEN, and BCL2.
• Model evaluation: Supports evaluation of model systems, including evidence that human iPSC-derived neurons are relevant for studying proteins like TDP-43 and BCL2 in conditions such as amyotrophic lateral sclerosis.

Methodology:

Systematic quality control of proteomic data; integration with published protein-protein interaction datasets to identify cell-type-independent and cell-type-specific interaction patterns; and joint analysis of genetic datasets with proteomic data to elucidate protein roles in disease contexts.