A multi-omics data simulator for complex disease studies and its application to evaluate multi-omics data analysis methods for disease classification | Zendy

RenHua Chung | Zendy; Chen-Yu Kang | Zendy

Open Access

A multi-omics data simulator for complex disease studies and its application to evaluate multi-omics data analysis methods for disease classification

Author(s) -

RenHua Chung,

Chen-Yu Kang

Publication year - 2019

Publication title -

gigascience

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.947

H-Index - 54

ISSN - 2047-217X

DOI - 10.1093/gigascience/giz045

Subject(s) - omics , epigenomics , proteomics , genomics , computational biology , metabolomics , biology , bioinformatics , computer science , dna methylation , genome , genetics , gene , gene expression

An integrative multi-omics analysis approach that combines multiple types of omics data including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and microbiomics has become increasing popular for understanding the pathophysiology of complex diseases. Although many multi-omics analysis methods have been developed for complex disease studies, only a few simulation tools that simulate multiple types of omics data and model their relationships with disease status are available, and these tools have their limitations in simulating the multi-omics data.

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