NAguideR

NAguideR provides missing-value imputation and evaluation for mass spectrometry (MS)-based quantitative proteomics datasets to support accurate downstream quantitative analyses.

Key Features:

• Integration of Imputation Methods: Incorporates 23 missing-value imputation algorithms applicable to MS-based proteomics data.
• Evaluation Criteria: Implements two categories of evaluation: classic computational metrics and proteomic empirical criteria that assess quantitative consistency across peptide charge-states, peptides belonging to the same proteins, and proteins within complexes and functional interactions.

Scientific Applications:

• Imputation selection and benchmarking: Enables evaluation and comparison of missing-value imputation methods in MS-based quantitative proteomics datasets.
• Application to DIA-MS label-free datasets: Applied to three label-free proteomic datasets generated by data independent acquisition mass spectrometry (DIA-MS), including peptide-level, protein-level, and phosphoproteomic variables with substantial biological replicates to discriminate optimal and sub-optimal imputation methods.

Methodology:

Implements 23 missing-value imputation algorithms and evaluates them using classic computational metrics and proteomic empirical criteria assessing charge-states, peptide-to-protein consistency, and proteins within complexes and functional interactions.