Shijia Zhu, PhD

Dr. Zhu’s lab is a dry lab. The research interests are as follows: 

• Develop novel computational methods to enhance the power of new technologies, e.g., spatial/single-cell multi-omics, 3rd generation sequencing, etc.
• Develop novel computational methods to screen the pathogenic upstream regulator and advance understanding of the complex genetic diseases.
• Conduct rigorous and reproducible integrative multi-modality data analysis (generated from spatially resolved sequencing, single-cell sequencing, long-read and short-read bulk sequencing, etc.) to shed light on the coordinated biological regulatory mechanism from different omics layers.
• Software:

1. Zhu, S. (2019). STIE: Spatial Transcriptome Image and Expression integration enables single-cell level spatial transcriptomics data analysis.
2. Zhu, S. (2018). GIGSEA: Genotype Imputed Gene Set Enrichment Analysis using GWAS Summary Level Data.
github.com/zhushijia/GIGSEAdata
3. Zhu, S. (2018). MatrixEpistasis: An ultrafast exhaustive epistasis scan for quantitative traits with covariate adjustment.
github.com/fanglab/MatrixEpistasis
4. Zhu, S. (2018). STAR2bSMRT: STARlong and STARshort based Single Molecule Real Time Iso-Seq analysis.
github.com/zhushijia/STAR2bSMRT
5. Zhu, S. (2017). SMRTER: Single Molecule Real Time sequencing Epigenetic Refinement.
github.com/fanglab/smrter
6. Zhu, S. (2015). HMDBN. Hidden Markov induced Dynamic Bayesian Network for recovering time-evolving gene regulatory networks.
github.com/zhushijia/HMDBN