1. q-Diffusion leverages the full dimensionality of gene coexpression in single-cell transcriptomics.
- Author
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Marmarelis, Myrl G., Littman, Russell, Battaglin, Francesca, Niedzwiecki, Donna, Venook, Alan, Ambite, Jose-Luis, Galstyan, Aram, Lenz, Heinz-Josef, and Ver Steeg, Greg
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TRANSCRIPTOMES , *CLINICAL trials , *GENE libraries , *CYTOLOGY , *RNA sequencing , *RAS oncogenes - Abstract
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. The q-diffusion method uses the full dimensionality of gene coexpression in transcriptomics and benchmarking shows improvment of scRNAseq analyses. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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