@misc{10481/74389,
year = {2022},
month = {3},
url = {http://hdl.handle.net/10481/74389},
abstract = {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 theWallenius
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.},
organization = {FEDER/Junta de Andalucia-Consejeria de Economia y Conocimiento	CV20-36723},
organization = {MCIN/AEI	PID2020-119032RB-I00},
organization = {FEDER/Junta de Andalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades	P20_00335},
publisher = {MDPI},
keywords = {Gene set analysis},
keywords = {Regulation},
keywords = {Web tool},
keywords = {Enrichment analysis},
keywords = {Functional analysis},
title = {Functional Enrichment Analysis of Regulatory Elements},
doi = {10.3390/biomedicines10030590},
author = {García Moreno, Adrián and López Domínguez, Raúl and Villatoro García, Juan Antonio and Ramírez Mena, Alberto and Aparicio Puerta, Ernesto Luis and Hackenberg, Michael and Carmona Sáez, Pedro},
}