通过基于熵的稀疏 PCA（结合超图和融合相似性）准确识别单细胞类型

IF 1.2 4区数学 Q2 STATISTICS & PROBABILITY

Journal of Applied Statistics Pub Date : 2024-07-21 DOI:10.1080/02664763.2024.2369955

Juan Wang, Tai-Ge Wang, Shasha Yuan, Feng Li

引用次数: 0

摘要

单细胞 RNA 测序（scRNA-seq）技术的出现使研究人员能够深入了解细胞的异质性。然而，scRNA-seq 数据的高维度和噪声给研究人员带来了困难。

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Accurate identification of single-cell types via correntropy-based Sparse PCA combining hypergraph and fusion similarity

The advent of single-cell RNA sequencing (scRNA-seq) technology enables researchers to gain deep insights into cellular heterogeneity. However, the high dimensionality and noise of scRNA-seq data p...

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来源期刊

Journal of Applied Statistics 数学-统计学与概率论

CiteScore

3.40

自引率

0.00%

发文量

126

审稿时长

6 months

期刊介绍： Journal of Applied Statistics provides a forum for communication between both applied statisticians and users of applied statistical techniques across a wide range of disciplines. These areas include business, computing, economics, ecology, education, management, medicine, operational research and sociology, but papers from other areas are also considered. The editorial policy is to publish rigorous but clear and accessible papers on applied techniques. Purely theoretical papers are avoided but those on theoretical developments which clearly demonstrate significant applied potential are welcomed. Each paper is submitted to at least two independent referees.