cv

PhD

Shanghai Jiao Tong University

Bioinformatics

• Metaproteomics
• Cancer microbiome
• Deep learning
• Peptides

Master

Shanghai Jiao Tong University

Bioinformatics

• Metaproteomics
• Cancer microbiome

Bachelor

University of Electronic Science and Technology of China

Bioinformatics

Evaluation of imputation and imputation-free strategies for differential abundance analysis in metaproteomics data

Briefings in Bioinformatics

We systematically evaluated five imputation methods [sample minimum, quantile regression, k-nearest neighbors (KNN), Bayesian principal component analysis (bPCA), random forest (RF)] and six imputation-free methods (moderated t-test, two-part t-test, two-part Wilcoxon test, semiparametric differential abundance analysis, differential abundance analysis with Bayes shrinkage estimation of variance method, and Mixture) for differential analysis in simulated metaproteomic datasets based on both data-dependent acquisition MS experiments and emerging data-independent acquisition experiments.