Marker-specific pixel attribution for single-cell protein quantification with PixAQ
- 1National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian 361102, China.; School of Informatics, Xiamen University, Xiamen 3
Abstract
Imaging mass cytometry (IMC) typically quantifies all markers within the same cell mask, although their signals have distinct spatial distributions. This quantification method may omit relevant signals or include signals from neighboring cells. We present PixAQ, which improves single-cell protein quantification in IMC through marker-specific probabilistic pixel attribution. PixAQ combines spatial proximity with anchor-group intensity models to assign pixel-marker observations among neighboring cells and an explicit residual component. Original intensities are averaged over marker-specific supports. Across three cohorts (680 regions), comparisons in 366 patients showed improved agreement with predefined population-marker relationships, with cohort-median patient-paired gains of 1.99 to 4.83 percentage points in expected-marker share over shared-mask quantification. Ablation analyses showed that both spatial and intensity evidence contributed to these gains. Conventional and high-resolution IMC images linked supports to visible local and intracellular signal structures. PixAQ improves single-cell protein quantification by determining which local signals contribute to each marker measurement without changing cell segmentation.
Related
- scRBP infers cell-specific RNA-binding protein regulons from single-cell transcriptomes at gene and isoform resolution
- Recurrent and system-specific model-attribution patterns in PISA 2022 science performance across nine education systems
- Reproducible detection of antigen-specific T cells and Tregs via standardized and automated activation-induced marker assay workflows
- Attribution-based diagnostics for single-cell foundation models
- Accurate quantification of protein concentrations and state populations by 2D 1H-N Q-BEST NMR
BibTeX
@misc{zha2026markerspecific,
title = {{Marker-specific pixel attribution for single-cell protein quantification with PixAQ}},
author = {Y. Zha and C. Liang and Y. Lin and G. Li and C. Zhang and Z. Huang and Z. Wang and L. Zhang and M. Tong and W. Jiang and X. Xiao and R. Yu},
howpublished = {bioRxiv},
year = {2026},
month = nov,
doi = {10.64898/2026.11.03.763929},
url = {https://www.biorxiv.org/content/10.64898/2026.11.03.763929v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Marker-specific pixel attribution for single-cell protein quantification with PixAQ
AU - Y. Zha
AU - C. Liang
AU - Y. Lin
AU - G. Li
AU - C. Zhang
AU - Z. Huang
AU - Z. Wang
AU - L. Zhang
AU - M. Tong
AU - W. Jiang
AU - X. Xiao
AU - R. Yu
PY - 2026
DA - 2026/11/03
PB - bioRxiv
DO - 10.64898/2026.11.03.763929
UR - https://www.biorxiv.org/content/10.64898/2026.11.03.763929v1
AB - Imaging mass cytometry (IMC) typically quantifies all markers within the same cell mask, although their signals have distinct spatial distributions. This quantification method may omit relevant signals or include signals from neighboring cells. We present PixAQ, which improves single-cell protein quantification in IMC through marker-specific probabilistic pixel attribution. PixAQ combines spatial proximity with anchor-group intensity models to assign pixel-marker observations among neighboring cells and an explicit residual component. Original intensities are averaged over marker-specific supports. Across three cohorts (680 regions), comparisons in 366 patients showed improved agreement with predefined population-marker relationships, with cohort-median patient-paired gains of 1.99 to 4.83 percentage points in expected-marker share over shared-mask quantification. Ablation analyses showed that both spatial and intensity evidence contributed to these gains. Conventional and high-resolution IMC images linked supports to visible local and intracellular signal structures. PixAQ improves single-cell protein quantification by determining which local signals contribute to each marker measurement without changing cell segmentation.
ER -