August 6, 2024Nature CommunicationsOpen Access

Robust analysis of allele-specific copy number alterations from scRNA-seq data with XClone

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The XClone framework robustly identifies allele-specific copy number alterations in sparse single-cell data, resolving complex tumor subclones without loss of resolution.
Statistical smoothing across cell neighborhood and gene coordinate graphs strengthens signals of read depth and allelic imbalance from sparse scRNA-seq transcriptomic datasets.
Validation across challenging cancer datasets highlights potential detection of whole genome duplication, enabling dissection of subclonal evolution and phenotypic diversity.

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Computational analysis reveals allele-specific copy number alterations in complex cancer transcriptomes, highlighting subclonal architecture and whole genome duplication.

Cite This Study

Huang et al. (2024) studied this question.

synapsesocial.com/papers/68e5d477b6db64358756a6ee https://doi.org/10.1038/s41467-024-51026-0

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Implication

Computational analysis reveals allele-specific copy number alterations in complex cancer transcriptomes, highlighting subclonal architecture and whole genome duplication.

Robust analysis of allele-specific copy number alterations from scRNA-seq data with XClone

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Implication

Cite This Study

Robust analysis of allele-specific copy number alterations from scRNA-seq data with XClone

Key Points

Discussion

Implication

Cite This Study

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