scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics

Making sense of the rapidly growing single-cell omics datasets available is limited by difficulties in leveraging disparate datasets in analyses. Here, the authors present scGCN, a graph based convolutional network to allow effective knowledge transfer across omics datasets.

Bibliographic Details
Main Authors:	Qianqian Song, Jing Su, Wei Zhang
Format:	Article
Language:	English
Published:	Nature Publishing Group 2021-06-01
Series:	Nature Communications
Online Access:	https://doi.org/10.1038/s41467-021-24172-y

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spelling	doaj-bbbe438249ed4e82920ea7ff27f115342021-06-27T11:11:34ZengNature Publishing GroupNature Communications2041-17232021-06-0112111110.1038/s41467-021-24172-yscGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omicsQianqian Song0Jing Su1Wei Zhang2Center for Cancer Genomics and Precision Oncology, Wake Forest Baptist Comprehensive Cancer Center, Wake Forest Baptist Medical CenterDepartment of Biostatistics and Health Data Science, Indiana University School of MedicineCenter for Cancer Genomics and Precision Oncology, Wake Forest Baptist Comprehensive Cancer Center, Wake Forest Baptist Medical CenterMaking sense of the rapidly growing single-cell omics datasets available is limited by difficulties in leveraging disparate datasets in analyses. Here, the authors present scGCN, a graph based convolutional network to allow effective knowledge transfer across omics datasets.https://doi.org/10.1038/s41467-021-24172-y
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Qianqian Song Jing Su Wei Zhang
spellingShingle	Qianqian Song Jing Su Wei Zhang scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics Nature Communications
author_facet	Qianqian Song Jing Su Wei Zhang
author_sort	Qianqian Song
title	scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics
title_short	scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics
title_full	scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics
title_fullStr	scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics
title_full_unstemmed	scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics
title_sort	scgcn is a graph convolutional networks algorithm for knowledge transfer in single cell omics
publisher	Nature Publishing Group
series	Nature Communications
issn	2041-1723
publishDate	2021-06-01
description	Making sense of the rapidly growing single-cell omics datasets available is limited by difficulties in leveraging disparate datasets in analyses. Here, the authors present scGCN, a graph based convolutional network to allow effective knowledge transfer across omics datasets.
url	https://doi.org/10.1038/s41467-021-24172-y
work_keys_str_mv	AT qianqiansong scgcnisagraphconvolutionalnetworksalgorithmforknowledgetransferinsinglecellomics AT jingsu scgcnisagraphconvolutionalnetworksalgorithmforknowledgetransferinsinglecellomics AT weizhang scgcnisagraphconvolutionalnetworksalgorithmforknowledgetransferinsinglecellomics
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scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics

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