ttgump/scDeepCluster_pytorch
Pytorch implementation of scDeepCluster for Single Cell RNA-seq data
This tool helps single-cell biologists and researchers analyze gene expression data from single-cell RNA sequencing (scRNA-seq) experiments. It takes your raw scRNA-seq cell-by-gene count matrix and identifies distinct cell populations, outputting predicted cell cluster labels and lower-dimensional representations of your data for visualization. This is ideal for researchers studying cellular heterogeneity and identifying novel cell types.
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Use this if you need to identify distinct cell populations within your single-cell RNA sequencing data, especially when integrating data from multiple experimental batches.
Not ideal if you are not working with single-cell RNA sequencing data or do not need to perform cell clustering analysis.
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Language
Jupyter Notebook
License
Apache-2.0
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Last pushed
Jul 10, 2024
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