Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2023.04.03.535352v1?rss=1
Authors: Huang, R., Huang, X., Tong, Y., Yan, H. Y. N., Leung, S. Y., Stegle, O., Huang, Y.
Abstract:
Somatic copy number variations (CNVs) are major mutations in various cancers for their development and clonal progression. A few computational methods have been proposed to detect CNVs from single-cell transcriptomic data. Still, the technical sparsity makes it challenging to identify allele-specific CNVs, especially in complex clonal structures. Here we present a statistical method, XClone, to detect haplotype-aware CNVs by integrating expression levels and allelic balance from scRNA-seq data. With well-annotated datasets on multiple cancer types, we demonstrated that XClone could accurately detect different types of allele-specific CNVs, enabling the discovery of the corresponding subclones and dissection of their phenotypic impacts.
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