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numbat

Haplotype-Aware CNV Analysis from scRNA-Seq

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>.

README

# Numbat

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Numbat is a haplotype-aware CNV caller from single-cell and spatial transcriptomics data. It integrates signals from gene expression, allelic ratio, and population-derived haplotype information 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 scRNA-seq and spatial transcriptomics
 2. Differentiate tumor versus normal cells in the tumor microenvironment 
 3. Infer the clonal architecture and evolutionary history of profiled tumors. 

![image](https://user-images.githubusercontent.com/13375875/153020818-2e782689-09db-427f-ad98-2c175021a936.png)

Numbat does not require paired DNA or genotype data and operates solely on the donor scRNA-seq data (for example, 10x Cell Ranger output). For details of the method, please checkout our paper:

> [Teng Gao, Ruslan Soldatov, Hirak Sarkar, Adam Kurkiewicz, Evan Biederstedt, Po-Ru Loh, Peter Kharchenko. Haplotype-aware analysis of somatic copy number variations from single-cell transcriptomes. Nature Biotechnology (2022).](https://www.nature.com/articles/s41587-022-01468-y)

## Numbat-multiome
Numbat was later extended to multi-modality (single-cell RNA and ATAC) data. Check out the [vignette](https://kharchenkolab.github.io/numbat/articles/numbat-multiome.html) and paper below:

> [Ruitong Li, Jean-Baptiste Alberge, Tina Keshavarzian, Junko Tsuji, Johan Gustafsson, Mahshid Rahmat, Elizabeth D Lightbody, Stephanie L Deng, Santiago Riviero, Mendy Miller, F Naz Cemre Kalayci, Adrian Wiestner, Clare Sun, Mathieu Lupien, Irene Ghobrial, Erin Parry, Teng Gao, Gad Getz. Numbat-multiome: inferring copy number variations by combining RNA and chromatin accessibility information from single-cell data. Briefings in Bioinformatics (2025).](https://academic.oup.com/bib/article/26/5/bbaf516/8290422)


# User Guide
For a complete guide, please see [Numbat User Guide](https://kharchenkolab.github.io/numbat/).

# Questions?
We appreciate your feedback! Please raise a github [issue](https://github.com/kharchenkolab/numbat/issues) for bugs, questions and new feature requests. For bug reports, please attach full log, error message, input parameters, and ideally a reproducible example (if possible).

Versions across snapshots

VersionRepositoryFileSize
1.5.2 rolling linux/jammy R-4.5 numbat_1.5.2.tar.gz 4.1 MiB
1.5.2 rolling linux/noble R-4.5 numbat_1.5.2.tar.gz 4.1 MiB
1.5.2 rolling source/ R- numbat_1.5.2.tar.gz 4.1 MiB
1.5.2 latest linux/jammy R-4.5 numbat_1.5.2.tar.gz 4.1 MiB
1.5.2 latest linux/noble R-4.5 numbat_1.5.2.tar.gz 4.1 MiB
1.5.2 latest source/ R- numbat_1.5.2.tar.gz 4.1 MiB
1.5.2 2026-04-26 source/ R- numbat_1.5.2.tar.gz 4.1 MiB
1.5.2 2026-04-23 source/ R- numbat_1.5.2.tar.gz 4.1 MiB
1.4.2 2025-04-20 source/ R- numbat_1.4.2.tar.gz 3.8 MiB

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