Explore AI Agent Skills & Claude Prompts

Calculates pathway activity scores for metabolic pathways across different cell groups and subsets. This process quantifies the metabolic activity of each pathway per group, generating visualizations (heatmaps and violin plots) to compare metabolic states between clusters or conditions. Based on the methodology from Xiao et al.

scrnametaboliclandscape

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, pathway activity calculation, and heterogeneity analysis. Based on methodology from Xiao et al.

cellcellcommunicationplots

Visualize cell-cell communication inference results from CellCellCommunication process. Creates publication-ready network diagrams, heatmaps, and interaction plots to help interpret ligand-receptor interactions between cell types.

markersfinder

Flexible marker finding process that wraps Seurat's FindMarkers function for custom group comparisons beyond simple cluster-vs-all analysis. Unlike ClusterMarkers (all-vs-all cluster comparisons), MarkersFinder enables targeted differential expression analysis between specific groups, conditions within cell types, or any custom comparison defined by metadata columns. Automatically performs pathway enrichment analysis on significant markers and generates comprehensive visualizations.

metabolicfeatures

Performs enrichment analysis (GSEA-based) for metabolic pathways across different cell groups to identify significantly enriched pathways. Uses fast gene set enrichment analysis (fgsea package) to rank pathways by their association with specific clusters, conditions, or cell states. Generates summary plots and enrichment visualizations for biological interpretation.

metabolicpathwayheterogeneity

Analyzes metabolic pathway heterogeneity within cell populations by calculating normalized enrichment scores (NES) for each pathway across different groups. Quantifies metabolic diversity and identifies pathways with variable activity patterns. Uses principal component analysis and GSEA to assess pathway heterogeneity, revealing subpopulation-specific metabolic states and transitions.

tessa

TESSA (TCR and Expression Joint Clustering) is a Bayesian model that integrates T-cell receptor (TCR) sequence profiling with transcriptomes of T cells. It maps the functional landscape of the TCR repertoire by learning unified representations across modalities. The process employs BriseisEncoder to capture TCR sequence features, creating numerical embeddings that reconstruct Atchley Factor matrices and CDR3 sequences.

topexpressinggenesofallcells

Identifies and visualizes the top expressing genes per cluster across ALL cells (before T/B cell selection), followed by pathway enrichment analysis. Provides initial overview of all cell populations by highlighting the most highly expressed genes and their biological functions.

torbcellselection

Separates T and non-T cells or B and non-B cells from a mixed cell population. Uses either clonotype percentage from VDJ data, indicator gene expression (CD3 markers for T cells, CD19/CD20 for B cells), custom selector expressions, or k-means clustering for automatic selection.

cdr3aaphyschem

Analyzes physicochemical properties of CDR3 amino acid sequences to understand biochemical characteristics of T-cell receptor repertoires. Performs regression analysis between two cell groups at different CDR3 lengths for each physicochemical feature (hydrophobicity, volume, isoelectric point, etc.).

cdr3clustering

Cluster TCR/BCR clones by CDR3 sequences using GIANA or ClusTCR (both Faiss-based). Adds `CDR3_Cluster` column to metadata for clonotype analysis.

immunopipe-config

Master skill for generating immunopipe pipeline configurations. Determines pipeline architecture based on data type (scRNA-seq with or without scTCR/BCR-seq) and analysis requirements. Routes to individual process skills for detailed configuration. Use this skill when starting a new immunopipe configuration or modifying pipeline-level options.