ADTnorm: Robust Integration of Single-Cell Protein Measurement Across Cite-Seq Datasets

Authors

Ye Zheng
Daniel P Caron
Ju Yeong Kim
Seong-Hwan Jun
Yuan Tian
Florian Mair
Kenneth D Stuart
Peter A Sims
Raphael Gottardo

Publication Date

7-1-2025

Journal

Nature Communications

DOI

10.1038/s41467-025-61023-6

PMID

40595741

PMCID

PMC12218154

PubMedCentral® Posted Date

7-1-2025

PubMedCentral® Full Text Version

Post-print

Abstract

Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) enables paired measurement of surface protein and mRNA expression in single cells using antibodies conjugated to oligonucleotide tags. Due to the high copy number of surface protein molecules, sequencing antibody-derived tags (ADTs) allows for robust protein detection, improving cell-type identification. However, variability in antibody staining leads to batch effects in the ADT expression, obscuring biological variation, reducing interpretability, and obstructing cross-study analyses. Here, we present ADTnorm, a normalization and integration method designed explicitly for ADT abundance. Benchmarking against 14 existing scaling and normalization methods, we show that ADTnorm accurately aligns populations with negative- and positive-expression of surface protein markers across 13 public datasets, effectively removing technical variation across batches and improving cell-type separation. ADTnorm enables efficient integration of public CITE-seq datasets, each with unique experimental designs, paving the way for atlas-level analyses. Beyond normalization, ADTnorm includes built-in utilities to aid in automated threshold-gating as well as assessment of antibody staining quality for titration optimization and antibody panel selection. Applying ADTnorm to an antibody titration study, a published COVID-19 CITE-seq dataset, and a human hematopoietic progenitors study allowed for identifying previously undetected phenotype-associated markers, illustrating a broad utility in biological applications.

Keywords

Single-Cell Analysis, Humans, Antibodies, Transcriptome, Epitopes, Gene Expression Profiling, Membrane Proteins, High-Throughput Nucleotide Sequencing, COVID-19

Published Open-Access

yes

Recommended Citation

Zheng, Ye; Caron, Daniel P; Kim, Ju Yeong; et al., "ADTnorm: Robust Integration of Single-Cell Protein Measurement Across Cite-Seq Datasets" (2025). Faculty, Staff and Student Publications. 4954.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/4954