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Computational Tracking of Cell Origins Using CellSexID from Single-Cell Transcriptomes

GSE305521 Mus musculus Expression profiling by high throughput sequencing 6 samples Submitted 2025/08/16 Platform GPL24247
Summary
These datasets support the validation and biological application of CellSexID, a computational method for inferring cell origin in sex-mismatched settings using single-cell RNA sequencing (scRNA-seq) data. CellSexID leverages the expression of sex-linked genes to classify individual cells as male or female, providing an in silico alternative to physical labeling. Two scRNA-seq datasets from sex-mismatched chimeric mouse diaphragm models are included: (i) a validation dataset, in which cell multiplexing labels were applied to establish ground-truth cell origin, and (ii) an experimental dataset, analyzed without labels to demonstrate the method’s applicability in unlabeled settings. Together, these datasets provide a resource for benchmarking computational cell origin tracking methods and for studying immune cell populations in chimeric model systems.
Published in
Computational tracking of cell origins using CellSexID from single-cell transcriptomes
Tai H, Li Q, Wang J et al. · Cell reports methods 2025 · PMID 40967208 · doi:10.1016/j.crmeth.2025.101181
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Also filed as BioProject PRJNA1306179 and SRA study SRP609016. Searching any of these in the dataset finder brings you back here.

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