Critical review on data processing algorithms in non-target screening: challenges and opportunities to improve result...

Area of Science:

• Analytical Chemistry
• Environmental Chemistry

Background:

• Non-target screening (NTS) is crucial for identifying unknown compounds in complex environmental samples.
• High-resolution mass spectrometry enhances NTS but complicates data analysis.

Purpose of the Study:

• To review and understand Non-target screening (NTS) data processing methods.
• To discuss challenges and solutions for NTS data analysis, including algorithm performance and parameter optimization.

Main Methods:

• Focus on data processing steps: centroiding, extracted ion chromatogram (XIC) building, peak characterization, alignment, componentization, and feature prioritization.
• Analysis of algorithm strengths, weaknesses, and the impact of user parameters.
• Discussion of data quality, uncertainty, and cross-study comparability.

Main Results:

• Identified challenges in NTS data preprocessing, peak detection, and feature extraction.
• Highlighted the need for automated parameter optimization and robust data quality assessment.
• Proposed solutions for improved cross-study comparability, including standardized statistics and data exchange platforms.

Conclusions:

• NTS data processing requires careful consideration of algorithms, parameters, and data quality.
• Standardization and open data practices are essential for advancing NTS reliability and comparability.
• Future recommendations focus on algorithm development and user best practices for the NTS community.