DEEPsc

DeepSc is a software tool used for imputing spatial information onto single-cell RNA sequencing (scRNA-seq) data using a deep learning-based approach. It takes into account a spatial reference atlas and uses a system-adaptive model to map the scRNA-seq data to the reference atlas. The tool evaluates several metrics to assess its accuracy, precision, and robustness compared to other methods. Additionally, it provides a data-adaptive way to connect scRNA-seq datasets and spatial imaging datasets for analyzing cell fate decisions. The implementation of DeepSc includes a uniform API and is available as an open-source software.

Topic

Transcriptomics;Imaging;Mapping;Machine learning

Detail

  • Operation: Imputation;Essential dynamics;Splitting;Dimensionality reduction

  • Software interface: Command-line user interface

  • Language: MATLAB,Java

  • License: Not stated

  • Cost: Free of charge

  • Version name: -

  • Credit: NIH, NSF, the Simons Foundation.

  • Input: -

  • Output: -

  • Contact: Zixuan Cang zcang@uci.edu ,Qing Nie qnie@uci.edu

  • Collection: -

  • Maturity: -

Publications

  • DEEPsc: A Deep Learning-Based Map Connecting Single-Cell Transcriptomics and Spatial Imaging Data.
  • Maseda F, et al. DEEPsc: A Deep Learning-Based Map Connecting Single-Cell Transcriptomics and Spatial Imaging Data. DEEPsc: A Deep Learning-Based Map Connecting Single-Cell Transcriptomics and Spatial Imaging Data. 2021; 12:636743. doi: 10.3389/fgene.2021.636743
  • https://doi.org/10.3389/FGENE.2021.636743
  • PMID: 33833776
  • PMC: PMC8021700

Download and documentation


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