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
Documentation: https://github.com/fmaseda/DEEPsc/blob/main/README.md
Home page: https://github.com/fmaseda/DEEPsc
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