A computational method that infers copy number variations (CNVs) in cancer scRNA-seq data and reconstructs the tumor phylogeny. 'numbat' integrates signals from gene expression, allelic ratio, and population haplotype structures to accurately infer allele-specific CNVs in single cells and reconstruct their lineage relationship. 'numbat' can be used to: 1. detect allele-specific copy number variations from single-cells; 2. differentiate tumor versus normal cells in the tumor microenvironment; 3. infer the clonal architecture and evolutionary history of profiled tumors. 'numbat' does not require tumor/normal-paired DNA or genotype data, but operates solely on the donor scRNA-data data (for example, 10x Cell Ranger output). Additional examples and documentations are available at <https://kharchenkolab.github.io/numbat/>. For details on the method please see Gao et al. Nature Biotechnology (2022) <doi:10.1038/s41587-022-01468-y>.
Package details |
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Author | Teng Gao [cre, aut], Ruslan Soldatov [aut], Hirak Sarkar [aut], Evan Biederstedt [aut], Peter Kharchenko [aut] |
Maintainer | Teng Gao <tgaoteng@gmail.com> |
License | MIT + file LICENSE |
Version | 1.4.0 |
URL | https://github.com/kharchenkolab/numbat/ https://kharchenkolab.github.io/numbat/ |
Package repository | View on CRAN |
Installation |
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