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Cellector: A tool to detect foreign genotype cells in scRNAseq data with applications in leukemia and microchimerism
Haynes Heaton1, Reza Behboudi1, Collin Ward1
1Auburn University, Auburn, AL 36849.
Biorxiv : the Preprint Server for Biology
|April 10, 2026
Summary
Cellector accurately detects rare foreign cells, crucial for monitoring leukemia patients after hematopoietic cell transplant (HCT). This computational method identifies measurable residual disease (MRD) at very low percentages, aiding clinical decisions.
Area of Science:
- Genomics
- Computational Biology
- Oncology
Background:
- Rare genetically distinct cells are found in transplant patients, maternal-fetal microchimerism, and cancers.
- Detecting these cells is vital for understanding biological conditions, particularly in leukemia patients post-hematopoietic cell transplant (HCT).
- Measurable residual disease (MRD), identified by patient-genotype cells post-HCT, can indicate leukemia relapse and impacts clinical decision-making.
Purpose of the Study:
- To present Cellector, a novel computational method for identifying rare foreign genotype cells.
- To evaluate Cellector's accuracy in detecting microchimeric cells in single-cell RNA sequencing (scRNAseq) datasets.
Main Methods:
- Development of Cellector, a computational tool for analyzing scRNAseq data.
- Testing Cellector's ability to detect rare cells at low percentages.
Main Results:
- Cellector accurately identifies rare foreign genotype cells.
- The method demonstrates high sensitivity, detecting microchimeric cells present at 0.05% or lower.
Conclusions:
- Cellector is an effective computational method for detecting rare microchimeric cells.
- Accurate MRD detection using Cellector can significantly aid clinical decision-making for leukemia patients post-HCT.
