CellMAGE: cell-type deconvolution for multi-parent population analysis of gene expression
- 1The Jackson Laboratory
Abstract
Single-cell RNA-sequencing remains prohibitively expensive for multiparental population (MPP) studies. Existing deconvolution methods treat bulk RNA-seq as genetically anonymous mixtures, but in MPPs, the proportional contribution of each parental strain to each progeny's transcriptome is already known. CellMAGE (Cell-type deconvolution for Multi-parent Analysis of Gene Expression) weights parental cell-type profiles by each progeny's known genetic composition, requiring no model training and no minimum sample size. Validated in 16 Diversity Outbred mice across 12 prefrontal cortex cell types and 23,116 genes, predicted and measured gene expression were statistically equivalent (0.05) in all cell types (pooled Spearman = 0.923, 95% CI: 0.910, 0.934). CIBERSORTx required 96 additional samples to resolve at most 12.4% of genes and only 3 cell types; CellMAGE outperformed it even within this restricted comparison (per-cell-type median : 0.908-0.974 vs. 0.353-0.641). CellMAGE is applicable to any MPP with parental single-cell data, including diploid crop MAGIC populations.
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BibTeX
@misc{ball2026cellmage,
title = {{CellMAGE: cell-type deconvolution for multi-parent population analysis of gene expression}},
author = {R. L. Ball and A. Klein and A. A. Auth and D. A. Skelly and H. He and V. M. Philip and L. H. Gagnon and E. J. Chesler},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.08.750196},
url = {https://www.biorxiv.org/content/10.64898/2026.09.08.750196v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - CellMAGE: cell-type deconvolution for multi-parent population analysis of gene expression
AU - R. L. Ball
AU - A. Klein
AU - A. A. Auth
AU - D. A. Skelly
AU - H. He
AU - V. M. Philip
AU - L. H. Gagnon
AU - E. J. Chesler
PY - 2026
DA - 2026/09/08
PB - bioRxiv
DO - 10.64898/2026.09.08.750196
UR - https://www.biorxiv.org/content/10.64898/2026.09.08.750196v1
AB - Single-cell RNA-sequencing remains prohibitively expensive for multiparental population (MPP) studies. Existing deconvolution methods treat bulk RNA-seq as genetically anonymous mixtures, but in MPPs, the proportional contribution of each parental strain to each progeny's transcriptome is already known. CellMAGE (Cell-type deconvolution for Multi-parent Analysis of Gene Expression) weights parental cell-type profiles by each progeny's known genetic composition, requiring no model training and no minimum sample size. Validated in 16 Diversity Outbred mice across 12 prefrontal cortex cell types and 23,116 genes, predicted and measured gene expression were statistically equivalent (0.05) in all cell types (pooled Spearman = 0.923, 95% CI: 0.910, 0.934). CIBERSORTx required 96 additional samples to resolve at most 12.4% of genes and only 3 cell types; CellMAGE outperformed it even within this restricted comparison (per-cell-type median : 0.908-0.974 vs. 0.353-0.641). CellMAGE is applicable to any MPP with parental single-cell data, including diploid crop MAGIC populations.
ER -