Bioinformatics | Single-cell | Spatial Omics | OmicVerse core contributor
- Single-cell transcriptomics (scRNA-seq)
- Spatial transcriptomics & spatial omics
- Cell-cell communication networks
- Gene co-expression network analysis (WGCNA)
- Tumor microenvironment & immune infiltration
- R/Bioconductor to Python porting with numerical parity
๐ ๏ธ My Projects in OmicVerse
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py-hdWGCNA Weighted Gene Co-expression Network Analysis Python | 3.1x faster than R | hME r=0.9999 |
py-Augur Cell Type Prioritization Python | 4.1x faster | Pearson r=0.9999 |
py-Statial Spatial Cell State Analysis Python | 13.6x faster | 93.8% function coverage |
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py-CellCall Intercellular Network Inference Python | 4.8x faster | Pearson >= 0.998 |
py-scmetabolism Single-cell Metabolism Analysis Python |
py-SigXTalk Pathway Crosstalk from Cell Communication Python | Deep Learning |
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py-SpaceTrooper QC for Image-based Spatial Transcriptomics Python |
py-spanorm Spatially-aware Normalisation Python | Spatial Transcriptomics |
py-spotsweeper Spatially-aware QC Outlier Detection Python | Spatial Transcriptomics |
- CDH2 as a Hub Gene Associated with Cisplatin Resistance and Prognosis in Ovarian Cancer - Int J Mol Sci (IF 5.6) | Code
- DOCK5 in High-Grade Serous Ovarian Carcinoma - Single-cell analysis of immune infiltration | Code
"Porting the R bioinformatics ecosystem to Python, one package at a time."

