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About SNPmanifold

SNPmanifold is a Python package that learns a representative manifold for single cells based on their SNPs (Single-Nucleotide Polymorphisms) using VAE (Variational AutoEncoder) and UMAP (Uniform Manifold Approximation and Projection). It takes AD matrix, DP matrix, and VCF (or variant_name.tsv) as inputs. You can compile them from bam file(s) either conveniently by cellSNP-lite or by your custom scripts.

SNPmanifold first performs simple filtering on AD matrix and DP matrix for high-quality cells and SNPs. It then trains VAE and UMAP to learn a representative manifold for single cells according to their allele frequency of different SNPs (AF = AD/DP). Finally, it classifies cells into clones and infer their phylogeny based on the manifold.

References

• Hoi Man Chung and Yuanhua Huang. Interpretable variational encoding of genotypes identifies comprehensive clonality and lineages in single cells geometrically. BioRxivto appear.