Accurate identification of locally aneuploid cells by incorporating cytogenetic information in single cell data analysis
- bgtaylor1
- Nov 22, 2024
- 2 min read

Date: | 15 October 2024 |
PMID: | N/A |
Category: | N/A |
Authors: | Ziyi Li, Ruoxing Li, Irene Ganan-Gomez, Hussein A. Abbas, Guillermo Garcia-Manero & Wei Sun |
Abstract: |
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Single-cell RNA sequencing is a powerful tool to investigate the cellular makeup of tumor samples. However, due to the sparse data and the complex tumor microenvironment, it can be challenging to identify neoplastic cells that play important roles in tumor growth and disease progression. This is especially relevant for blood cancers, where neoplastic cells may be highly similar to normal cells. To address this challenge, we have developed partCNV and partCNVH, two methods for rapid and accurate detection of aneuploid cells with local copy number deletion or amplification. PartCNV uses an expectation-maximization (EM) algorithm with mixtures of Poisson distributions and incorporates cytogenetic information to guide the classification. PartCNVH further improves partCNV by integrating a hidden Markov model for feature selection. We have thoroughly evaluated the performance of partCNV and partCNVH through simulation studies and real data analysis using three scRNA-seq datasets from blood cancer patients. Our results show that partCNV and partCNVH have favorable accuracy and provide more interpretable results compared to existing methods. In the real data analysis, we have identified multiple biological processes involved in the oncogenesis of myelodysplastic syndromes and acute myeloid leukemia.
Acknowledgements:
The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute, or the National Institute of Health.
The Translational and Basic Science Research in Early Lesions (TBEL) Research Consortia is supported and funded by grants from the National Cancer Institute and the National Institutes of Health under the following award numbers:
Project Number: | Awardee Organization |
U54CA274374 | Fred Hutchinson Cancer Center |
U54CA274375 | Houston Methodist Research Institute |
U54CA274370 | Johns Hopkins University |
U54CA274371 | UT MD Anderson Cancer Center |
U54CA274367 | Vanderbilt University Medical Center |



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