ANPELA

ANPELA evaluates label-free proteome quantification workflows by assessing and ranking LFQ processing pipelines to identify optimal workflows for proteomic and metaproteomic datasets.

Key Features:

• Workflow evaluation: Assesses entire LFQ workflows using five well-established criteria rooted in distinct theoretical frameworks.
• Data format compatibility: Automatically detects and handles diverse data formats generated by various quantification tools.
• Comprehensive processing methods: Implements an extensive set of LFQ processing methods exceeding those available on other servers and standalone tools.
• Performance ranking: Systematically ranks the performance of 560 potential LFQ workflows to identify dataset-specific optimal solutions.
• Validation with benchmarks: Validates workflow performance using metaproteomic benchmarks and spiked proteins to assess LFQ accuracy.

Scientific Applications:

• Metaproteomics: Supports analysis of microbial adaptive responses and interactions with external stimuli or host cells through optimized LFQ workflows.
• Workflow selection: Enables data-driven selection of optimal LFQ workflows tailored to specific proteomic datasets.
• General LFQ studies: Applies to other label-free quantification studies requiring comparative evaluation of quantification pipelines.

Methodology:

Computational assessment of LFQ workflows using five theoretical criteria, automatic detection and handling of diverse quantification data formats, application of an extensive set of processing methods, systematic ranking of 560 workflows, and validation using metaproteomic benchmarks and spiked proteins.