PSpecteR

PSpecteR visualizes LC-MS proteomics data to facilitate inspection of spectra, evaluation of peptide and protein sequence matches, and annotation for downstream analysis.

Key Features:

• Interactive visualization: Enables interactive inspection of LC-MS spectra, evaluation of spectral properties, testing of alternative peptide and protein sequence matches, and generation of annotated spectra.
• Support for multiple data processing steps: Reads multiple mass spectrometry file formats and integrates outputs from open-source database search engines to support different stages of proteomics data processing.
• Spectral labeling and modification testing: Labels spectra with fragmentation patterns and supports testing of post-translational modifications.
• Mapping and visualization of fragments and metadata: Plots identified fragments on reference sequences and visualizes algorithmic outputs together with associated metadata.
• Exportable outputs: Exports figures, tables, and spectra for sharing and publication.
• R-based flexible framework: Implemented in R and R Shiny to provide a flexible framework for extending analytical features.

Scientific Applications:

• Top-down and bottom-up proteomics visualization: Supports visualization and inspection of both top-down and bottom-up proteomics LC-MS datasets.
• Data quality assessment: Enables assessment of spectral quality and data integrity through inspection of spectral properties and fragmentation patterns.
• Exploratory data analysis: Facilitates exploratory analysis of proteomics datasets, including hypothesis generation and testing of alternative sequence matches.
• Publication preparation: Generates annotated spectra and exportable figures and tables for figure preparation in publications.

Methodology:

Implemented in R using the R Shiny framework; reads multiple mass spectrometry file formats; integrates outputs from open-source database search engines; performs spectral labeling and post-translational modification testing; plots fragments on reference sequences and visualizes algorithmic outputs with associated metadata.