RT Journal Article
T1 Functional Enrichment Analysis of Regulatory Elements.
A1 Garcia-Moreno, Adrian
A1 López-Domínguez, Raul
A1 Villatoro-García, Juan Antonio
A1 Ramirez-Mena, Alberto
A1 Aparicio-Puerta, Ernesto
A1 Hackenberg, Michael
A1 Pascual-Montano, Alberto
A1 Carmona-Saez, Pedro
K1 enrichment analysis
K1 functional analysis
K1 gene set analysis
K1 regulation
K1 web tool
AB 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.
SN 2227-9059
YR 2022
FD 2022-03-03
LK http://hdl.handle.net/10668/20822
UL http://hdl.handle.net/10668/20822
LA en
DS RISalud
RD Apr 7, 2025