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Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease.


ABSTRACT: We propose DEGAS (Diagnostic Evidence GAuge of Single cells), a novel deep transfer learning framework, to transfer disease information from patients to cells. We call such transferrable information "impressions," which allow individual cells to be associated with disease attributes like diagnosis, prognosis, and response to therapy. Using simulated data and ten diverse single-cell and patient bulk tissue transcriptomic datasets from glioblastoma multiforme (GBM), Alzheimer's disease (AD), and multiple myeloma (MM), we demonstrate the feasibility, flexibility, and broad applications of the DEGAS framework. DEGAS analysis on myeloma single-cell transcriptomics identified PHF19high myeloma cells associated with progression. Availability: https://github.com/tsteelejohnson91/DEGAS .

SUBMITTER: Johnson TS 

PROVIDER: S-EPMC8808996 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease.

Johnson Travis S TS   Yu Christina Y CY   Huang Zhi Z   Xu Siwen S   Wang Tongxin T   Dong Chuanpeng C   Shao Wei W   Zaid Mohammad Abu MA   Huang Xiaoqing X   Wang Yijie Y   Bartlett Christopher C   Zhang Yan Y   Walker Brian A BA   Liu Yunlong Y   Huang Kun K   Zhang Jie J  

Genome medicine 20220201 1


We propose DEGAS (Diagnostic Evidence GAuge of Single cells), a novel deep transfer learning framework, to transfer disease information from patients to cells. We call such transferrable information "impressions," which allow individual cells to be associated with disease attributes like diagnosis, prognosis, and response to therapy. Using simulated data and ten diverse single-cell and patient bulk tissue transcriptomic datasets from glioblastoma multiforme (GBM), Alzheimer's disease (AD), and m  ...[more]

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