MOSS: multi-omic integration with sparse value decomposition

被引：1

作者：

Gonzalez-Reymundez, Agustin ^{[1
]}

Grueneberg, Alexander ^{[1
]}

Lu, Guanqi ^{[1
]}

Alves, Filipe Couto ^{[1
]}

Rincon, Gonzalo ^{[2
]}

Vazquez, Ana, I ^{[1
]}

机构：

[1] Michigan State Univ, Dept Epidemiol & Biostat, E Lansing, MI 48824 USA

[2] Genus PLC Inc, Genome Sci R&D, De Forest, MI USA

来源：

BIOINFORMATICS | 2022年 / 38卷 / 10期

关键词：

PRINCIPAL COMPONENT ANALYSIS; BREAST; PREDICTION; JOINT;

D O I：

10.1093/bioinformatics/btac179

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

This article presents multi-omic integration with sparse value decomposition (MOSS), a free and open-source R package for integration and feature selection in multiple large omics datasets. This package is computationally efficient and offers biological insight through capabilities, such as cluster analysis and identification of informative omic features.

引用

页码：2956 / 2958

页数：3

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