De novo identification of expressed cancer somatic mutations from single-cell RNA sequencing data
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Identifying expressed somatic mutations from single-cell RNA sequencing data de novo is challenging but highly valuable. We propose RESA – Recurrently Expressed SNV Analysis, a computational framework to identify expressed somatic mutations from scRNA-seq data. RESA achieves an average precision of 0.77 on three in silico spike-in datasets.
Nội dung trích xuất từ tài liệu:
De novo identification of expressed cancer somatic mutations from single-cell RNA sequencing data
Nội dung trích xuất từ tài liệu:
De novo identification of expressed cancer somatic mutations from single-cell RNA sequencing data
Tìm kiếm theo từ khóa liên quan:
Genome Medicine Somatic mutations Single-cell RNA sequencing data Recurrently Expressed SNV Analysis High precisionTài liệu liên quan:
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