RT Journal Article
T1 Gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite.
A1 Jabato, Fernando M
A1 Córdoba-Caballero, José
A1 Rojano, Elena
A1 Romá-Mateo, Carlos
A1 Sanz, Pascual
A1 Pérez, Belén
A1 Gallego, Diana
A1 Seoane, Pedro
A1 Ranea, Juan A G
A1 Perkins, James R
AB High-throughput gene expression analysis is widely used. However, analysis is not straightforward. Multiple approaches should be applied and methods to combine their results implemented and investigated. We present methodology for the comprehensive analysis of expression data, including co-expression module detection and result integration via data-fusion, threshold based methods, and a Naïve Bayes classifier trained on simulated data. Application to rare-disease model datasets confirms existing knowledge related to immune cell infiltration and suggest novel hypotheses including the role of calcium channels. Application to simulated and spike-in experiments shows that combining multiple methods using consensus and classifiers leads to optimal results. ExpHunter Suite is implemented as an R/Bioconductor package available from https://bioconductor.org/packages/ExpHunterSuite . It can be applied to model and non-model organisms and can be run modularly in R; it can also be run from the command line, allowing scalability with large datasets. Code and reports for the studies are available from https://github.com/fmjabato/ExpHunterSuiteExamples .
YR 2021
FD 2021-07-23
LK http://hdl.handle.net/10668/18254
UL http://hdl.handle.net/10668/18254
LA en
DS RISalud
RD Apr 8, 2025