De novo detection of somatic variants in high-quality long-read single-cell RNA sequencing data.

ABSTRACT: In cancer, genetic and transcriptomic variations generate clonal heterogeneity, leading to treatment resistance. Long-read single-cell RNA sequencing (LR scRNA-seq) has the potential to detect genetic and transcriptomic variations simultaneously. Here, we present LongSom, a computational workflow leveraging high-quality LR scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), including in mitochondria (mtSNVs), copy number alterations (CNAs), and gene fusions, to reconstruct the tumor clonal heterogeneity. Before somatic variant calling, LongSom reannotates marker gene-based cell types using cell mutational profiles. LongSom distinguishes somatic SNVs from noise and germline polymorphisms by applying an extensive set of hard filters and statistical tests. Applying LongS

SUBMITTER: Dondi A 

PROVIDER: S-EPMC12047253 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature