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q-Diffusion leverages the full dimensionality of gene coexpression in single-cell transcriptomics.

Publication ,  Journal Article
Marmarelis, MG; Littman, R; Battaglin, F; Niedzwiecki, D; Venook, A; Ambite, J-L; Galstyan, A; Lenz, H-J; Ver Steeg, G
Published in: Commun Biol
April 2, 2024

Unlocking the full dimensionality of single-cell RNA sequencing data (scRNAseq) is the next frontier to a richer, fuller understanding of cell biology. We introduce q-diffusion, a framework for capturing the coexpression structure of an entire library of genes, improving on state-of-the-art analysis tools. The method is demonstrated via three case studies. In the first, q-diffusion helps gain statistical significance for differential effects on patient outcomes when analyzing the CALGB/SWOG 80405 randomized phase III clinical trial, suggesting precision guidance for the treatment of metastatic colorectal cancer. Secondly, q-diffusion is benchmarked against existing scRNAseq classification methods using an in vitro PBMC dataset, in which the proposed method discriminates IFN-γ stimulation more accurately. The same case study demonstrates improvements in unsupervised cell clustering with the recent Tabula Sapiens human atlas. Finally, a local distributional segmentation approach for spatial scRNAseq, driven by q-diffusion, yields interpretable structures of human cortical tissue.

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Published In

Commun Biol

DOI

EISSN

2399-3642

Publication Date

April 2, 2024

Volume

7

Issue

1

Start / End Page

400

Location

England

Related Subject Headings

  • Single-Cell Analysis
  • Leukocytes, Mononuclear
  • Humans
  • Gene Expression Profiling
  • Cluster Analysis
  • 32 Biomedical and clinical sciences
  • 31 Biological sciences
 

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Marmarelis, M. G., Littman, R., Battaglin, F., Niedzwiecki, D., Venook, A., Ambite, J.-L., … Ver Steeg, G. (2024). q-Diffusion leverages the full dimensionality of gene coexpression in single-cell transcriptomics. Commun Biol, 7(1), 400. https://doi.org/10.1038/s42003-024-06104-w
Marmarelis, Myrl G., Russell Littman, Francesca Battaglin, Donna Niedzwiecki, Alan Venook, Jose-Luis Ambite, Aram Galstyan, Heinz-Josef Lenz, and Greg Ver Steeg. “q-Diffusion leverages the full dimensionality of gene coexpression in single-cell transcriptomics.Commun Biol 7, no. 1 (April 2, 2024): 400. https://doi.org/10.1038/s42003-024-06104-w.
Marmarelis MG, Littman R, Battaglin F, Niedzwiecki D, Venook A, Ambite J-L, et al. q-Diffusion leverages the full dimensionality of gene coexpression in single-cell transcriptomics. Commun Biol. 2024 Apr 2;7(1):400.
Marmarelis, Myrl G., et al. “q-Diffusion leverages the full dimensionality of gene coexpression in single-cell transcriptomics.Commun Biol, vol. 7, no. 1, Apr. 2024, p. 400. Pubmed, doi:10.1038/s42003-024-06104-w.
Marmarelis MG, Littman R, Battaglin F, Niedzwiecki D, Venook A, Ambite J-L, Galstyan A, Lenz H-J, Ver Steeg G. q-Diffusion leverages the full dimensionality of gene coexpression in single-cell transcriptomics. Commun Biol. 2024 Apr 2;7(1):400.

Published In

Commun Biol

DOI

EISSN

2399-3642

Publication Date

April 2, 2024

Volume

7

Issue

1

Start / End Page

400

Location

England

Related Subject Headings

  • Single-Cell Analysis
  • Leukocytes, Mononuclear
  • Humans
  • Gene Expression Profiling
  • Cluster Analysis
  • 32 Biomedical and clinical sciences
  • 31 Biological sciences