cellstruct: Metrics scores to quantify the biological preservation between two embeddings

Loh, J. W.; Ouyang, J. F.

doi:10.1101/2023.11.13.566337

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bioRxiv · 10.1101/2023.11.13.566337

cellstruct: Metrics scores to quantify the biological preservation between two embeddings

Loh, J. W.·Ouyang, J. F.

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Abstract

Single-cell transcriptomics (scRNA-seq) is extensively applied in uncovering biological heterogeneity. There are different dimensionality reduction techniques, but it is unclear which method works best in preserving biological information when creating a two-dimensional embedding. Therefore, we implemented cellstruct, which calculates three metrics scores to quantify the global or local biological similarity between a two-dimensional and its corresponding higher-dimensional PCA embeddings at either single-cell or cluster level. These scores pinpoint cell populations with low biological information preservation, in addition to visualizing the cell-cell or cluster-cluster relationships in the PCA embedding. Two study cases illustrate the usefulness of cellstruct in exploratory data analysis.

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Loh, J. W., Ouyang, J. F.. 2023-11-14. cellstruct: Metrics scores to quantify the biological preservation between two embeddings. https://doi.org/10.1101/2023.11.13.566337

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