Protein complex-based analysis is resistant to the obfuscating consequences of batch effects --- a case study in...

Area of Science:

• Proteomics
• Bioinformatics
• Translational Research

Background:

• Batch effects in proteomics introduce technical variation, hindering clinical and translational research.
• Existing batch effect correction methods can be ineffective, compromise data integrity, and introduce false positives.

Purpose of the Study:

• To introduce and validate batch-effect resistant methods for proteomics data analysis.
• To demonstrate the efficacy of protein complex-based analyses in mitigating batch effects.

Main Methods:

• Utilized simulated and real proteomics data.
• Evaluated existing batch effect correction techniques and Principal Component Analysis (PCA).
• Introduced and assessed protein complex-based analysis as a batch-effect resistant approach.

Main Results:

• Standard batch effect correction and PCA methods may fail to remove all batch effects or can distort data.
• Protein complex-based analyses demonstrate innate resistance to subtle batch effects.
• These complex-based methods protect data integrity by avoiding data transformation.

Conclusions:

• Protein complex-based analyses provide high reproducibility and prediction accuracy in proteomics.
• These methods are inherently resistant to batch effects, preserving data integrity.
• The constituent proteins of identified complexes are strongly associated with phenotype, indicating clinical relevance.