Yafei Lyu

A statistical framework for measuring reproducibility and replicability of high-throughput experiments from multiple sources

The paper introduces a statistical model to measure reproducibility and replicability across replicate experiments in multi-source studies, using a nested copula mixture model.

MuSiC2: cell type deconvolution for multi-condition bulk RNA-seq data

MuSiC2 improves cell type proportion estimation in bulk RNA-seq data from different clinical conditions using an iterative method, outperforming traditional approaches.

Iterative transfer learning with neural network for clustering and cell type classification in single-cell RNA-seq analysis

ItClust improves clustering and cell type classification in scRNA-seq by using iterative transfer learning with neural networks, outperforming existing methods across diverse datasets.

Deep learning enables accurate clustering and batch effect removal in single-cell RNA-seq analysis

This paper introduces DESC, a deep learning method for single-cell clustering that improves accuracy and removes batch effects.

Integrative single-cell and bulk RNA-seq analysis in human retina identified cell type-specific composition and gene expression changes for age-related macular degeneration

The paper uses single-cell and bulk RNA-seq to analyze gene expression changes in human retina with AMD, identifying cell type-specific alterations.

Condition-adaptive fused graphical lasso (CFGL): an adaptive procedure for inferring condition-specific gene co-expression network

The paper introduces CFGL, a method for inferring condition-specific gene co-expression networks, showing improved accuracy and revealing biological insights in rat and cancer datasets.