tidyproteomics

tidyproteomics provides a standardized R data-object framework and modular functions for post-processing mass spectrometry-based quantitative proteomics data.

Key Features:

• Standardization and Interoperability: Standardizes quantitative proteomics data into a consistent R data-object structure that supports biological annotations and cross-platform integration.
• Modular Workflow Framework: Implements discrete, chainable functions that can be connected end-to-end to define complex analyses in small steps.
• Customization and Flexibility: Allows users to select function options, control the sequence of operations, and incorporate custom algorithms for tailored analyses.
• Data Exploration and Annotation: Structures datasets to accommodate biological annotations and simplify data exploration.
• Development of Additional Tools: Serves as a framework to develop and integrate additional analysis algorithms and tools.
• Time Efficiency: Provides analysis and plotting functions that reduce manual data manipulation time.

Scientific Applications:

• Standardized post-processing: Supports post-processing of mass spectrometry-based quantitative proteomics data, including sample group statistics, quantitative variation assessment, and data filtering.
• Sample group statistics: Enables computation of group-level statistics for comparative proteomics analyses.
• Quantitative variation assessment: Facilitates assessment of quantitative variation across samples.
• Data filtering and annotation: Enables filtering of quantitative datasets and incorporation of biological annotations.
• Workflow development and reproducibility: Provides a basis for constructing repeatable, modular analysis workflows and integrating custom algorithms.

Methodology:

Uses a simplified R data-object structure and discrete modular functions for post-processing, exploration, annotation, and plotting.