Numbat

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.

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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).

Numbat-multiome

Numbat was later extended to multi-modality (single-cell RNA and ATAC) data. Check out the vignette 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).

User Guide

For a complete guide, please see Numbat User Guide.

Questions?

We appreciate your feedback! Please raise a github issue 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).