ImmunoPheno: A Computational Framework for Data-Driven Design and Analysis of Immunophenotyping Experiments

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Authors: Lincoln Wu, Pablo G. Cámara, Kai Tan, Neil D. Romberg, Emylette Cruz Cabrera, Joseph S. Tumulty, Kyung Jin Ahn, Apoorva S. Joshi
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Abstract

This repository contains CODEX and CITE-seq datasets from three human tonsils obtained from immunocompetent healthy donors. Each CITE-seq dataset includes cell annotations generated using ImmunoPheno. All CITE-seq data, including annotations, are provided as Scanpy objects stored in .h5ad files. The CODEX data was processed using Seurat and include all intermediate components, such as count matrices, dimensionality reductions, cell embeddings, nearest-neighbor graphs, and spatial coordinates. The processed data is provided as a Seurat object stored in an .rds file. A separate CSV file containing cell annotations generated using ImmunoPheno for the CODEX dataset is also included. CITE-Seq Datasets Tonsil481_CITE_Seq_Scanpy.h5ad Tonsil498_CITE_Seq_Scanpy.h5ad Tonsil510_CITE_Seq_Scanpy.h5ad CODEX Datasets Tonsil498_CODEX_filtered_seurat_rawCounts.rds Tonsil498_CODEX_ImmunoPheno_Annotations.csv

Fields of Study & Subjects

Single-cell and spatial transcriptomics Cell Image Analysis Techniques T-cell and B-cell Immunology

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
28 January 2026
Document type
Dataset