Hybrid Clustering of Single-Cell Gene Expression and Spatial Information via Integrated NMF and K-Means

Advances in single cell transcriptomics have allowed us to study the identity of single cells. This has led to the discovery of new cell types and high resolution tissue maps of them. Technologies that measure multiple modalities of such data add more detail, but they also complicate data integratio...

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Autores principales:	Sooyoun Oh, Haesun Park, Xiuwei Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	single cell transcriptomics spatial locations cell identity non-negative matrix factorization data integration Genetics QH426-470
Acceso en línea:	https://doaj.org/article/5d7ec78a9dea4e1db4d2afb01d8c0e67
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spelling	oai:doaj.org-article:5d7ec78a9dea4e1db4d2afb01d8c0e672021-11-08T06:17:24ZHybrid Clustering of Single-Cell Gene Expression and Spatial Information via Integrated NMF and K-Means1664-802110.3389/fgene.2021.763263https://doaj.org/article/5d7ec78a9dea4e1db4d2afb01d8c0e672021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fgene.2021.763263/fullhttps://doaj.org/toc/1664-8021Advances in single cell transcriptomics have allowed us to study the identity of single cells. This has led to the discovery of new cell types and high resolution tissue maps of them. Technologies that measure multiple modalities of such data add more detail, but they also complicate data integration. We offer an integrated analysis of the spatial location and gene expression profiles of cells to determine their identity. We propose scHybridNMF (single-cell Hybrid Nonnegative Matrix Factorization), which performs cell type identification by combining sparse nonnegative matrix factorization (sparse NMF) with k-means clustering to cluster high-dimensional gene expression and low-dimensional location data. We show that, under multiple scenarios, including the cases where there is a small number of genes profiled and the location data is noisy, scHybridNMF outperforms sparse NMF, k-means, and an existing method that uses a hidden Markov random field to encode cell location and gene expression data for cell type identification.Sooyoun OhHaesun ParkXiuwei ZhangFrontiers Media S.A.articlesingle cell transcriptomicsspatial locationscell identitynon-negative matrix factorizationdata integrationGeneticsQH426-470ENFrontiers in Genetics, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	single cell transcriptomics spatial locations cell identity non-negative matrix factorization data integration Genetics QH426-470
spellingShingle	single cell transcriptomics spatial locations cell identity non-negative matrix factorization data integration Genetics QH426-470 Sooyoun Oh Haesun Park Xiuwei Zhang Hybrid Clustering of Single-Cell Gene Expression and Spatial Information via Integrated NMF and K-Means
description	Advances in single cell transcriptomics have allowed us to study the identity of single cells. This has led to the discovery of new cell types and high resolution tissue maps of them. Technologies that measure multiple modalities of such data add more detail, but they also complicate data integration. We offer an integrated analysis of the spatial location and gene expression profiles of cells to determine their identity. We propose scHybridNMF (single-cell Hybrid Nonnegative Matrix Factorization), which performs cell type identification by combining sparse nonnegative matrix factorization (sparse NMF) with k-means clustering to cluster high-dimensional gene expression and low-dimensional location data. We show that, under multiple scenarios, including the cases where there is a small number of genes profiled and the location data is noisy, scHybridNMF outperforms sparse NMF, k-means, and an existing method that uses a hidden Markov random field to encode cell location and gene expression data for cell type identification.
format	article
author	Sooyoun Oh Haesun Park Xiuwei Zhang
author_facet	Sooyoun Oh Haesun Park Xiuwei Zhang
author_sort	Sooyoun Oh
title	Hybrid Clustering of Single-Cell Gene Expression and Spatial Information via Integrated NMF and K-Means
title_short	Hybrid Clustering of Single-Cell Gene Expression and Spatial Information via Integrated NMF and K-Means
title_full	Hybrid Clustering of Single-Cell Gene Expression and Spatial Information via Integrated NMF and K-Means
title_fullStr	Hybrid Clustering of Single-Cell Gene Expression and Spatial Information via Integrated NMF and K-Means
title_full_unstemmed	Hybrid Clustering of Single-Cell Gene Expression and Spatial Information via Integrated NMF and K-Means
title_sort	hybrid clustering of single-cell gene expression and spatial information via integrated nmf and k-means
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/5d7ec78a9dea4e1db4d2afb01d8c0e67
work_keys_str_mv	AT sooyounoh hybridclusteringofsinglecellgeneexpressionandspatialinformationviaintegratednmfandkmeans AT haesunpark hybridclusteringofsinglecellgeneexpressionandspatialinformationviaintegratednmfandkmeans AT xiuweizhang hybridclusteringofsinglecellgeneexpressionandspatialinformationviaintegratednmfandkmeans
_version_	1718442912196329472

Hybrid Clustering of Single-Cell Gene Expression and Spatial Information via Integrated NMF and K-Means

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