Gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite.

ABSTRACT: 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

SUBMITTER: Jabato FM 

PROVIDER: S-EPMC8302605 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature