stPlus: a reference-based method for the accurate enhancement of spatial transcriptomics.
stPlus: a reference-based method for the accurate enhancement of spatial transcriptomics.
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stPlus：一种基于参考的方法，用于精确增强空间转录组学
DOI：
10.1093/bioinformatics/btab298
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发表时间：
2021-07-12
期刊：
影响因子：
--
通讯作者：
Rui J
中科院分区：
文献类型：
--
作者：
Shengquan C;Boheng Z;Xiaoyang C;Xuegong Z;Rui J
Motivation Single-cell RNA sequencing (scRNA-seq) techniques have revolutionized the investigation of tran-scriptomic landscape in individual cells. Recent advancements in spatial transcriptomic technologies further enable gene expression profiling and spatial organization mapping of cells simultaneously. Among the tech-nologies, imaging-based methods can offer higher spatial resolutions, while they are limited by either the small number of genes imaged or the low gene detection sensitivity. Although several methods have been proposed for enhancing spatially resolved transcriptomics, inadequate accuracy of gene expression prediction and in-sufficient ability of cell-population identification still impede the applications of these methods. Results We propose stPlus, a reference-based method that leverages information in scRNA-seq data to enhance spatial transcriptomics. Based on an auto-encoder with a carefully tailored loss function, stPlus performs joint embedding and predicts spatial gene expression via a weighted k-NN. stPlus outperforms baseline meth-ods with higher gene-wise and cell-wise Spearman correlation coefficients. We also introduce a clustering-based approach to assess the enhancement performance systematically. Using the data enhanced by stPlus, cell populations can be better identified than using the measured data. The predicted expression of genes unique to scRNA-seq data can also well characterize spatial cell heterogeneity. Besides, stPlus is robust and scalable to datasets of diverse gene detection sensitivity levels, sample sizes, and number of spatially meas-ured genes. We anticipate stPlus will facilitate the analysis of spatial transcriptomics. Availability stPlus with detailed documents is freely accessible at http://health.tsinghua.edu.cn/software/stPlus/ and the source code is openly available on https://github.com/xy-chen16/stPlus. Contact ruijiang@tsinghua.edu.cn Supplementary information Supplementary data are available at Bioinformatics online.
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影响因子：
14.9
作者：
Gene Ontology Consortium
通讯作者：
Gene Ontology Consortium
影响因子：
64.5
作者：
Levine JH;Simonds EF;Bendall SC;Davis KL;Amir el-AD;Tadmor MD;Litvin O;Fienberg HG;Jager A;Zunder ER;Finck R;Gedman AL;Radtke I;Downing JR;Pe'er D;Nolan GP
通讯作者：
Nolan GP
下丘脑前区域的分子，空间和功能性单细胞分析。
DOI：
10.1126/science.aau5324
发表时间：
2018-11-16
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Moffitt JR;Bambah-Mukku D;Eichhorn SW;Vaughn E;Shekhar K;Perez JD;Rubinstein ND;Hao J;Regev A;Dulac C;Zhuang X
通讯作者：
Zhuang X
影响因子：
64.5
作者：
Davie K;Janssens J;Koldere D;De Waegeneer M;Pech U;Kreft Ł;Aibar S;Makhzami S;Christiaens V;Bravo González-Blas C;Poovathingal S;Hulselmans G;Spanier KI;Moerman T;Vanspauwen B;Geurs S;Voet T;Lammertyn J;Thienpont B;Liu S;Konstantinides N;Fiers M;Verstreken P;Aerts S
通讯作者：
Aerts S
影响因子：
64.8
作者：
Tasic B;Yao Z;Graybuck LT;Smith KA;Nguyen TN;Bertagnolli D;Goldy J;Garren E;Economo MN;Viswanathan S;Penn O;Bakken T;Menon V;Miller J;Fong O;Hirokawa KE;Lathia K;Rimorin C;Tieu M;Larsen R;Casper T;Barkan E;Kroll M;Parry S;Shapovalova NV;Hirschstein D;Pendergraft J;Sullivan HA;Kim TK;Szafer A;Dee N;Groblewski P;Wickersham I;Cetin A;Harris JA;Levi BP;Sunkin SM;Madisen L;Daigle TL;Looger L;Bernard A;Phillips J;Lein E;Hawrylycz M;Svoboda K;Jones AR;Koch C;Zeng H
通讯作者：
Zeng H