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Functional Enrichment Analysis of Regulatory Elements

by López-Domínguez, Raul , Villatoro-García, Juan Antonio , Garcia-Moreno, Adrian , Hackenberg, Michael , Pascual-Montano, Alberto , Ramirez-Mena, Alberto , Carmona-Saez, Pedro , Aparicio-Puerta, Ernesto

in Algorithms / Annotations / Arrhythmia / Bias / Bioinformatics / Data collection / DNA methylation / enrichment analysis / functional analysis / Gene expression / gene set analysis / Gene set enrichment analysis / Genomes / Information processing / Ontology / Proteins / regulation / Regulatory sequences / Statistics / Transcription factors / web tool

2022

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2022

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2022

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Journal Article

Functional Enrichment Analysis of Regulatory Elements

López-Domínguez, Raul,

Villatoro-García, Juan Antonio,

Garcia-Moreno, Adrian,

Hackenberg, Michael,

Pascual-Montano, Alberto,

Ramirez-Mena, Alberto,

Carmona-Saez, Pedro,

Aparicio-Puerta, Ernesto

2022

Overview

Statistical methods for enrichment analysis are important tools to extract biological information from omics experiments. Although these methods have been widely used for the analysis of gene and protein lists, the development of high-throughput technologies for regulatory elements demands dedicated statistical and bioinformatics tools. Here, we present a set of enrichment analysis methods for regulatory elements, including CpG sites, miRNAs, and transcription factors. Statistical significance is determined via a power weighting function for target genes and tested by the Wallenius noncentral hypergeometric distribution model to avoid selection bias. These new methodologies have been applied to the analysis of a set of miRNAs associated with arrhythmia, showing the potential of this tool to extract biological information from a list of regulatory elements. These new methods are available in GeneCodis 4, a web tool able to perform singular and modular enrichment analysis that allows the integration of heterogeneous information.

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Publisher

MDPI AG,MDPI

Subject

/ Bias