Quantify immune cell composition and signature activity from expression data.
npx skills add https://github.com/inflexa-ai/inflexa --skill immune-profiling
Please help me install this Agent Skill. Skill: immune-profiling Source: https://github.com/inflexa-ai/inflexa/tree/main/skills/immune-profiling Command: npx skills add https://github.com/inflexa-ai/inflexa --skill immune-profiling
This skill addresses the complexity of quantifying immune cell populations and characterizing the tumor microenvironment from omics data, ensuring reproducible and auditable analysis.
Use the immune-profiling skill to perform immune deconvolution on the provided expression matrix and generate a heatmap of cell type proportions.
High-intent search queries and answers about installing and using this skill.
Estimate immune cell fractions from bulk RNA-seq by applying validated deconvolution methods like MCP-counter, xCell, and EPIC to your standardized expression matrix to quantify immune populations and analyze tumor microenvironment states.
Analyze TCR and BCR repertoire diversity from single-cell expression data to evaluate adaptive immune responses, assessing clonality and diversity to understand immune repertoire dynamics in translational research.
Assess immune checkpoint expression and cytolytic activity by calculating immune signature scores using curated gene sets, enabling characterization of immune activation states within the tumor microenvironment.
Yes, standardized expression inputs are required, typically managed with anndata and pandas, while rpy2 bridges Python with R to utilize established bioinformatics methods for robust immune deconvolution.
Immune deconvolution handles tumor microenvironment characterization by quantifying immune cell composition and signature activity from transcriptomics data, supporting checkpoint profiling and reproducible immune assessment for oncology research.
Generate a heatmap of cell type proportions from transcriptomics data using matplotlib and seaborn to visualize the estimated immune cell fractions derived from your bulk or single-cell expression matrix.
TianGzlabDeconvolve bulk RNA-seq data with NNLS to estimate cell type proportions.
tassiovaleAnalyze gene lists or ranked data for enriched biological pathways and gene sets.
omicverseAnnotate tumor single-cell AnnData objects with MetaTiME cell-state labels.
ya-wayEstimate cell-type proportions in spatial transcriptomics spots using scRNA-seq references.
