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

共 50 条

[31] Integration of multi-omic data identifies psoriasis endotypes correlating with clinical and immunological phenotypes
Cameron, M.
Golden, J.
Richardson, B.
Damiani, G.
Ali, M.
Young, A.
Nichols, C.
Ward, N.
McCormick, T.
Cooper, K.
JOURNAL OF INVESTIGATIVE DERMATOLOGY, 2019, 139 (09) : S230 - S230
[32] Multi-Omic Data Integration Suggests Putative Microbial Drivers of Aetiopathogenesis in Mycosis Fungoides
Licht, Philipp
Mailaender, Volker
CANCERS, 2024, 16 (23)
[33] Multi-omic integration by machine learning (MIMaL) (vol 38, pg 4908, 2022)
Dickinson, Quinn
Aufschnaiter, Andreas
Ott, Martin
Meyer, Jesse G.
BIOINFORMATICS, 2023, 39 (04)
[34] GDC: Integration of Multi-Omic and Phenotypic Resources to Unravel the Genetic Pathogenesis of Hearing Loss
Cheng, Hui
Wang, Xuegang
Zhong, Mingjun
Geng, Jia
Li, Wenjian
Pei, Kanglu
Wang, Jing
Wang, Lanchen
Lu, Yu
Cheng, Jing
Bu, Fengxiao
Yuan, Huijun
ADVANCED SCIENCE, 2025,
[35] Multi-omic integration via similarity network fusion to detect molecular subtypes of ageing
Yang, Mu
Matan-Lithwick, Stuart
Wang, Yanling
De Jager, Philip L.
Bennett, David A.
Felsky, Daniel
BRAIN COMMUNICATIONS, 2023, 5 (02)
[36] A novel multivariate curve resolution based strategy for multi-omic integration of toxicological data
Menendez-Pedriza, Albert
Navarro-Martin, Laia
Jaumot, Joaquim
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2023, 242
[37] PyLiger: scalable single-cell multi-omic data integration in Python']Python
Lu, Lu
Welch, Joshua D.
BIOINFORMATICS, 2022, 38 (10) : 2946 - 2948
[38] inMTSCCA: An Integrated Multi-task Sparse Canonical Correlation Analysis for Multi-omic Brain Imaging Genetics
Du, Lei
Zhang, Jin
Zhao, Ying
Shang, Muheng
Guo, Lei
Han, Junwei
GENOMICS PROTEOMICS & BIOINFORMATICS, 2023, 21 (02) : 396 - 413
[39] Multi-omic profiling in pulmonary arterial hypertension
Otero-Nunez, Pablo
Rhodes, Christopher
Wharton, John
Swietlik, Emilia
Kariotis, Sokratis
Harbaum, Lars
Dunning, Mark
Elinoff, Jason
Errington, Niamh
Thomson, Roger
Iremonger, James
Coghlan, Gerry
Corris, Paul
Howard, Luke
Kiely, David
Church, Colin
Pepke-Zaba, Joanna
Toshner, Mark
Wort, Stephen
Desai, Ankit
Humbert, Marc
Nichols, William
Southgate, Laura
Tregouet, David-Alexandre
Trembath, Richard
Prokopenko, Inga
Graf, Stefan
Morrell, Nicholas
Wang, Dennis
Lawrie, Allan
Wilkins, Martin
EUROPEAN RESPIRATORY JOURNAL, 2020, 56
[40] Characterizing Multi-omic Data in Systems Biology
Mason, Christopher E.
Porter, Sandra G.
Smith, Todd M.
SYSTEMS ANALYSIS OF HUMAN MULTIGENE DISORDERS, 2014, 799 : 15 - 38

← 1 2 3 4 5 →