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CaClust: linking genotype to transcriptional heterogeneity of follicular lymphoma using BCR and exomic variants (K4B)

GSE252687 Homo sapiens Expression profiling by high throughput sequencing 4 samples Submitted 2024/10/03 Platform GPL20301
Summary
Tumours exhibit high genotypic and transcriptional heterogeneity. Both affect cancer progression and treatment, but have been predominantly studied separately in follicular lymphoma. To comprehensively investigate the evolution and genotype-to-phenotype maps in follicular lymphoma, we introduce CaClust, a probabilistic graphical model integrating deep whole exome, single-cell RNA and B-cell receptor sequencing data to infer clone genotypes, cell-to-clone mapping, and single-cell genotyping. CaClust outperforms a state-of-the-art model on simulated and patient data. In-depth analyses of single cells from four samples showcase effects of driver mutations, follicular lymphoma evolution, possible therapeutic targets, and single-cell genotyping that agrees with an independent targeted resequencing experiment.
Published in
CaClust: linking genotype to transcriptional heterogeneity of follicular lymphoma using BCR and exomic variants
Oksza-Orzechowski K, Quinten E, Shafighi S et al. · Genome biology 2024 · PMID 39501370 · doi:10.1186/s13059-024-03417-1
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Also filed as BioProject PRJNA1062045 and SRA study SRP482315. Searching any of these in the dataset finder brings you back here.

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