Merging microarray studies to identify a common gene expression signature to several structural heart diseases.

ABSTRACT:

Background

Heart disease is the leading cause of death worldwide. Knowing a gene expression signature in heart disease can lead to the development of more efficient diagnosis and treatments that may prevent premature deaths. A large amount of microarray data is available in public repositories and can be used to identify differentially expressed genes. However, most of the microarray datasets are composed of a reduced number of samples and to obtain more reliable results, several datasets have to be merged, which is a challenging task. The identification of differentially expressed genes is commonly done using statistical methods. Nonetheless, these methods are based on the definition of an arbitrary threshold to select the differentially expressed genes and there is no consensus o

SUBMITTER: Fajarda O 

PROVIDER: S-EPMC7346458 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature