Publications

A full list of publications can be found at my Google Scholar or ORCID pages.

1. Statistical Methods for Single-cell & Spatial Omics

Single-cell RNA-seq Analysis

• TORC: Reference construction for supervised celltype in scRNA-seq — Genome Biology, 2025 [Paper] [Software]
• scCTS: Single-cell cell type-specific analysis — Genome Biology, 2024 [Paper] [Software]
• Cellcano: Automated cell type classification for single-cell data — Nature Communications, 2023 [Paper] [Software]
• SC2P: Differential expression for scRNA-seq using mixture models — Bioinformatics, 2018 [Paper] [Software]
• FEAST: Feature selection for improved cell clustering — Bioinformatics, 2020 [Paper] [Software]
• WIND: New evaluation metric for cell clustering — Genome Biology, 2020 [Paper] [Software]

Spatial Transcriptomics

• SIGLE: Spot level representation learning in spatial transcriptomics — Genome Biology, 2025 [Paper] [Software]
• MicroMap: Predicting spatial expression from H&E images — 2026+ [Paper] [Code]

2. Signal Deconvolution for Bulk Omics Data

Cell Type-Specific Inference

• CeDAR: Cell type specific differential analysis with cell type hierarchy — Genome Biology, 2023 [Paper] [Software]
• TOAST: Reference-free cell type deconvolution — Genome Biology, 2019 [Paper] [Software]
• Cell type-specific differential analysis from bulk data — Bioinformatics, 2019 [Paper] [Software]

Tumor Purity Estimation

• InfiniumPurity: Tumor purity estimation from DNA methylation data — Genome Biology, 2016 [Paper] [Software]

3. Differential Analysis for Bulk Omics Data

Differential Methylation (BS-seq)

• DSS: Differential methylation for general experimental design — Bioinformatics, 2016 [Paper] [Software]
• DSS: DMR detection for single replicate BS-seq data — Nucleic Acids Research, 2015 [Paper] [Software]
• DSS: Differential methylation analysis for BS-seq data (two-group comparison) — Nucleic Acids Research, 2014 [Paper] [Software]

Differential Expression (RNA-seq)

• A new shrinkage estimator for dispersion improves differential expression detection — Biostatistics, 2012 [Paper] [Code]
• Sample size calculation for RNA-seq: Power evaluation and experimental design — Bioinformatics, 2015 [Paper] [Software]

Differential Peak Analysis (ChIP-seq)

• ChIPComp: Differential peak detection for ChIP-seq data — Bioinformatics, 2015 [Paper] [Software]

Software Tools

Bioconductor

• DSS — Differential methylation analysis for BS-seq data
• TOAST — Reference-free cell type deconvolution
• ChIPComp — Differential peak detection for ChIP-seq
• PROPER — Power evaluation for RNA-seq

CRAN

• InfiniumPurify — Tumor purity estimation from DNA methylation data

GitHub

• Cellcano — Automated cell type classification
• scCTS — Single-cell cell type-specific analysis
• SIGLE — Spot level representation learning in ST
• TORC — Reference construction for supervised celltype
• CeDAR — Cell type specific differential analysis
• Wind — Evaluation metric for cell clustering
• FEAST — Feature selection for cell clustering
• SC2P — Differential expression for scRNA-seq