Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data
Clustering cells based on similarities in gene expression is the first step towards identifying cell types in scRNASeq data. Here the authors incorporate biological knowledge into the clustering step to facilitate the biological interpretability of clusters, and subsequent cell type identification.
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Nature Portfolio
2021
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oai:doaj.org-article:5d61bdf78def44fd9d00e5d1ec5fd2c22021-12-02T16:36:00ZModel-based deep embedding for constrained clustering analysis of single cell RNA-seq data10.1038/s41467-021-22008-32041-1723https://doaj.org/article/5d61bdf78def44fd9d00e5d1ec5fd2c22021-03-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-22008-3https://doaj.org/toc/2041-1723Clustering cells based on similarities in gene expression is the first step towards identifying cell types in scRNASeq data. Here the authors incorporate biological knowledge into the clustering step to facilitate the biological interpretability of clusters, and subsequent cell type identification.Tian TianJie ZhangXiang LinZhi WeiHakon HakonarsonNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-12 (2021) |
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Science Q Tian Tian Jie Zhang Xiang Lin Zhi Wei Hakon Hakonarson Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data |
description |
Clustering cells based on similarities in gene expression is the first step towards identifying cell types in scRNASeq data. Here the authors incorporate biological knowledge into the clustering step to facilitate the biological interpretability of clusters, and subsequent cell type identification. |
format |
article |
author |
Tian Tian Jie Zhang Xiang Lin Zhi Wei Hakon Hakonarson |
author_facet |
Tian Tian Jie Zhang Xiang Lin Zhi Wei Hakon Hakonarson |
author_sort |
Tian Tian |
title |
Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data |
title_short |
Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data |
title_full |
Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data |
title_fullStr |
Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data |
title_full_unstemmed |
Model-based deep embedding for constrained clustering analysis of single cell RNA-seq data |
title_sort |
model-based deep embedding for constrained clustering analysis of single cell rna-seq data |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/5d61bdf78def44fd9d00e5d1ec5fd2c2 |
work_keys_str_mv |
AT tiantian modelbaseddeepembeddingforconstrainedclusteringanalysisofsinglecellrnaseqdata AT jiezhang modelbaseddeepembeddingforconstrainedclusteringanalysisofsinglecellrnaseqdata AT xianglin modelbaseddeepembeddingforconstrainedclusteringanalysisofsinglecellrnaseqdata AT zhiwei modelbaseddeepembeddingforconstrainedclusteringanalysisofsinglecellrnaseqdata AT hakonhakonarson modelbaseddeepembeddingforconstrainedclusteringanalysisofsinglecellrnaseqdata |
_version_ |
1718383635469434880 |