Accurate identification of locally aneuploid cells by incorporating cytogenetic information in single cell data analysis.

ABSTRACT: 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 hidde

SUBMITTER: Li Z 

PROVIDER: S-EPMC11480446 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature