: a tool for integrated differential expression analysis.

One of the fundamental aspects of genomic research is the identification of differentially expressed (DE) genes between two conditions. In the past decade, numerous DE analysis tools have been developed, employing various normalization methods and statistical modelling approaches. In this article, we introduce , an R package that leverages the capabilities of four state-of-the-art DE tools: edgeR, limma, DESeq2, and dearseq. returns the outputs of the four tools with a single command line, thus providing a simplified way for non-expert users to perform DE analysis. Furthermore, provides a statistically combined output of the four tools, and validations support the improved performance of these combination approaches for the detection of DE genes in small datasets. Finally, offers comprehensive and well-documented plots and tables at each stage of the analysis, thus facilitating result interpretation. Although has been designed with the intention of being accessible to users without extensive expertise in bioinformatics or statistics, the underlying code is open source and structured in such a way that it can be customized by advanced users to meet their specific requirements. is freely available for download from https://gitlab.com/soc-fogg-cro-aviano/DElite.