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immunology-assays

Computational analysis of immunology experimental data. ATAC-seq differential accessibility, immune cell tracking from microscopy, ELISA data processing with 4-parameter logistic fitting, immunohistochemistry quantification, antibody titer analysis, and cell cycle phase duration estimation. For flow cytometry use flow-cytometry-analysis; for scRNA-seq use scanpy.

backend/cli/skills/biology/immunology-assays/SKILL.md

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# Immunology Assays: Experimental Data Analysis

## Overview

Immunology Assays provides computational tools for analyzing data from common immunology experiments. This skill covers ATAC-seq differential accessibility analysis (MACS2 peak calling, motif enrichment), ELISA data processing with 4-parameter logistic standard curve fitting, immune cell tracking from time-lapse microscopy, immunohistochemistry (IHC) quantification with H-score calculation, antibody titer determination from serial dilution ELISA, cell cycle phase duration estimation from dual-nucleoside labeling, and multiplex cytokine assay data processing.

## When to Use This Skill

- Processing ELISA plate data with standard curve fitting (4PL)
- Quantifying IHC staining intensity (H-score, positive pixel percentage)
- Analyzing ATAC-seq peaks and differential chromatin accessibility
- Tracking immune cell migration from microscopy time-lapse data
- Determining antibody titers from serial dilution experiments
- Estimating cell cycle phase durations from pulse-labeling data