MOVICS: an R package for multi-omics integration and visualization in cancer subtyping
Author(s) -
Xiaofan Lu,
Jialin Meng,
Yujie Zhou,
Liyun Jiang,
Fangrong Yan
Publication year - 2020
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btaa1018
Subject(s) - subtyping , computer science , omics , visualization , context (archaeology) , cluster analysis , interface (matter) , data mining , bioinformatics , machine learning , biology , programming language , paleontology , bubble , maximum bubble pressure method , parallel computing
Stratification of cancer patients into distinct molecular subgroups based on multi-omics data is an important issue in the context of precision medicine. Here, we present MOVICS, an R package for multi-omics integration and visualization in cancer subtyping. MOVICS provides a unified interface for 10 state-of-the-art multi-omics integrative clustering algorithms, and incorporates the most commonly used downstream analyses in cancer subtyping researches, including characterization and comparison of identified subtypes from multiple perspectives, and verification of subtypes in external cohort using two model-free approaches for multiclass prediction. MOVICS also creates feature rich customizable visualizations with minimal effort. By analysing two published breast cancer cohort, we signifies that MOVICS can serve a wide range of users and assist cancer therapy by moving away from the 'one-size-fits-all' approach to patient care.
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