Browse published AI skills maintained by pwwang. Compare skill descriptions and follow each source repository for setup instructions.
Indexed skills
33Repository stars across indexed skills
660Repository forks
132Average repository stars per indexed skill
20Repository stars may repeat across skills from the same repository.
Imputes missing/dropout values in scRNA-seq expression data to improve metabolic pathway analysis. This process handles sparsity common in single-cell RNA sequencing data by filling in zero values using advance...
Annotates cell clusters with biological cell type labels using multiple methods: direct assignment, ScType, scCATCH, hitype, or CellTypist. This process is essential for interpreting clustering results by assig...
Comprehensive metabolic landscape analysis pipeline for scRNA-seq data. This is an all-in-one process group performing complete metabolic pathway analysis including expression imputation, feature selection, pat...
Performs coarse clustering on ALL cells (including T cells, B cells, and non-T/B cells) before cell type selection. This process identifies broad cell populations to enable subsequent T/B cell selection via `TO...
Finds marker genes for clusters of ALL cells before T/B cell selection. This process identifies differentially expressed genes across unsupervised clusters to help identify broad cell types (T cells, B cells, M...
Finds differentially expressed genes (markers) for clusters of T/B cells using Seurat's FindMarkers function. Performs statistical testing between clusters, identifies cluster-defining genes, and automatically...
Performs pseudo-bulk differential gene expression analysis using DESeq2 or edgeR. Aggregates single-cell counts to sample-level pseudo-bulk data, then identifies differentially expressed genes between condition...
Analyzes metabolic pathway heterogeneity within cell populations by calculating normalized enrichment scores (NES) for each pathway across different groups. Quantifies metabolic diversity and identifies pathway...
Infer ligand-receptor interactions and cell-cell communication networks from single-cell RNA-seq data using the LIANA+ framework. Identifies potential signaling events between cell types based on gene expressio...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.